1 00:00:02,279 --> 00:00:08,920 Speaker 1: We're gonna chack one almond, see how much it weighs. Okay, 2 00:00:10,160 --> 00:00:13,039 Speaker 1: I'm not happy with the size of this almond because 3 00:00:13,080 --> 00:00:19,040 Speaker 1: it's touching the edges of the capsule. So I'm gonna 4 00:00:19,120 --> 00:00:25,400 Speaker 1: take a smaller piece, once smaller. So I'm standing in 5 00:00:25,440 --> 00:00:30,720 Speaker 1: a government laboratory in Beltsville, Maryland with Teresa Henderson, a 6 00:00:30,800 --> 00:00:35,800 Speaker 1: scientist with the US Department of Agriculture. She's sizing up 7 00:00:35,840 --> 00:00:38,800 Speaker 1: a zip block bag of almonds that I brought here 8 00:00:38,840 --> 00:00:42,720 Speaker 1: with me as a snack. I've just asked her if 9 00:00:42,760 --> 00:00:46,640 Speaker 1: we could do a little experiment to figure out how 10 00:00:46,640 --> 00:00:50,600 Speaker 1: many calories are in my almonds A half one, because 11 00:00:50,600 --> 00:00:56,200 Speaker 1: that might be too small where I can be cut it. 12 00:01:01,640 --> 00:01:06,600 Speaker 1: Calories are everywhere. They're listed on the packaging of your 13 00:01:06,680 --> 00:01:10,440 Speaker 1: favorite junk food and on the menus at chain restaurants. 14 00:01:11,440 --> 00:01:15,720 Speaker 1: Apps like my fitness Pal and new exists mainly to 15 00:01:15,880 --> 00:01:20,600 Speaker 1: track exactly how many calories you eat each day. There 16 00:01:20,640 --> 00:01:23,679 Speaker 1: are numbers that a lot of us spend a lot 17 00:01:23,800 --> 00:01:29,039 Speaker 1: of time considering. I know I do. A banana has 18 00:01:29,200 --> 00:01:35,160 Speaker 1: about a hundred calories. A slice of bacon, haste, if 19 00:01:35,240 --> 00:01:40,640 Speaker 1: you can eat just one. These numbers are treated like gospel, 20 00:01:41,800 --> 00:01:45,880 Speaker 1: But have you ever stopped to think where do they 21 00:01:45,920 --> 00:01:50,960 Speaker 1: come from? Figuring that out is what brought me here 22 00:01:51,640 --> 00:01:55,400 Speaker 1: to this U. S. D A lab. This was the 23 00:01:55,440 --> 00:01:59,480 Speaker 1: start of a journey into the world of diets, where 24 00:01:59,560 --> 00:02:02,320 Speaker 1: I quit clely learned that a lot of the things 25 00:02:02,480 --> 00:02:06,920 Speaker 1: we think of as fact are a lot more complicated, 26 00:02:07,760 --> 00:02:12,840 Speaker 1: including the calorie. But first, back to our little science 27 00:02:12,919 --> 00:02:19,880 Speaker 1: experiment with Teresa. She's about to explode my almond literally 28 00:02:20,760 --> 00:02:25,079 Speaker 1: to figure out how many calories are in it. A 29 00:02:25,200 --> 00:02:29,360 Speaker 1: little chap. Teresa is chopping up my almond to prepare 30 00:02:29,400 --> 00:02:34,919 Speaker 1: it for a machine called a bomb calorimeter. It's this big, 31 00:02:35,120 --> 00:02:39,480 Speaker 1: boxy gray thing about the size of a printer. Put 32 00:02:39,560 --> 00:02:45,000 Speaker 1: my two thirds of an almond in there, and it weighs. 33 00:02:47,600 --> 00:02:51,160 Speaker 1: Teresa puts the almond in a small, shallow tray called 34 00:02:51,200 --> 00:02:56,160 Speaker 1: a combustion capsule. The tray gets connected to a fuse 35 00:02:56,240 --> 00:03:00,440 Speaker 1: wire and the whole thing is lowered into a metal 36 00:03:00,480 --> 00:03:05,760 Speaker 1: container inside the machine. This is the bomb part of 37 00:03:05,880 --> 00:03:12,280 Speaker 1: bomb calorimeter. The bomb is surrounded by water. The water 38 00:03:12,720 --> 00:03:16,680 Speaker 1: is going to heat up, and however hot it gets 39 00:03:17,200 --> 00:03:21,040 Speaker 1: will tell us how many calories my almond has. And 40 00:03:21,080 --> 00:03:26,120 Speaker 1: now it's starting so it's equilibrating and going through its process. 41 00:03:27,240 --> 00:03:31,280 Speaker 1: For a few minutes, it's quiet. All I can hear 42 00:03:31,680 --> 00:03:40,160 Speaker 1: is a low hump. The beeping means an electric current 43 00:03:40,240 --> 00:03:44,520 Speaker 1: is going to pass through the fuse wire and explode 44 00:03:44,720 --> 00:03:48,960 Speaker 1: my snack. You might expect blowing up an almond to 45 00:03:49,040 --> 00:03:54,000 Speaker 1: make a big bang, noise or something, but it actually doesn't. 46 00:03:56,000 --> 00:04:02,680 Speaker 1: It should be. We'll find out if it worked correctly, 47 00:04:02,880 --> 00:04:06,320 Speaker 1: the almond would be gone. Ah, temperature is going up. 48 00:04:06,400 --> 00:04:10,560 Speaker 1: That's a good sign. But what does blowing up my 49 00:04:10,640 --> 00:04:15,120 Speaker 1: almond have to do with calories? So it's just basically, 50 00:04:15,320 --> 00:04:17,200 Speaker 1: if you throw a log of wood on a fire, 51 00:04:17,720 --> 00:04:20,200 Speaker 1: it's going to burn and give off heat. Right, it's 52 00:04:20,200 --> 00:04:23,520 Speaker 1: the same concept. You're throwing, you know, a measured amount 53 00:04:23,640 --> 00:04:28,400 Speaker 1: of food or whatever and burning it, and it's going 54 00:04:28,440 --> 00:04:30,720 Speaker 1: to give off heat, and you're measuring the amount of 55 00:04:31,279 --> 00:04:36,280 Speaker 1: fuel energy in that food bomb. Calorimeter prints out a 56 00:04:36,320 --> 00:04:40,200 Speaker 1: little white paper that looks like a receipt. Teresa tears 57 00:04:40,240 --> 00:04:44,960 Speaker 1: it off and reads the result. My single almond contains 58 00:04:45,080 --> 00:04:51,720 Speaker 1: about seven calories. She opens up the machine. There's nothing 59 00:04:51,800 --> 00:04:56,120 Speaker 1: left but a few black smudges. You can see that 60 00:04:56,200 --> 00:05:02,320 Speaker 1: almond burnt very nicely, my snack is gone. But don't 61 00:05:02,320 --> 00:05:06,360 Speaker 1: write that number in your food log just yet. Calories 62 00:05:06,400 --> 00:05:11,120 Speaker 1: are way more complicated than our little experiment might suggest. 63 00:05:12,040 --> 00:05:16,320 Speaker 1: I'm going to get into that soon. First, let's start 64 00:05:16,360 --> 00:05:22,280 Speaker 1: with a more basic question. What is a calorie anyway? 65 00:05:22,600 --> 00:05:26,720 Speaker 1: And where do the calorie counts on foods come from? 66 00:05:26,760 --> 00:05:29,440 Speaker 1: What's the calorie? Calorie? Is something that makes it belly fat? 67 00:05:29,560 --> 00:05:31,520 Speaker 1: How they figure it out? I don't know. You just 68 00:05:31,560 --> 00:05:33,560 Speaker 1: read the can and that's how much calories is in 69 00:05:33,600 --> 00:05:36,840 Speaker 1: the food? I have no clue. I used to think 70 00:05:36,880 --> 00:05:40,160 Speaker 1: that there was a method where they I don't. I 71 00:05:40,200 --> 00:05:45,480 Speaker 1: don't know. I could only guess. Calories represent how much 72 00:05:45,600 --> 00:05:49,440 Speaker 1: energy there is in food. Energy your body then uses 73 00:05:49,600 --> 00:05:52,960 Speaker 1: to do all the things it does in a day. 74 00:05:53,440 --> 00:05:56,480 Speaker 1: I think of it like fuel in a car's gas tank. 75 00:05:57,600 --> 00:06:01,760 Speaker 1: Calories power your walk to the off this, cooking dinner 76 00:06:01,800 --> 00:06:06,440 Speaker 1: when you get home, even reading your kids a bedtime story. Wow, 77 00:06:06,560 --> 00:06:09,039 Speaker 1: the only thing I like. I'll X I'll google it. 78 00:06:09,480 --> 00:06:12,800 Speaker 1: How many calories is in one egg? How many calories 79 00:06:12,880 --> 00:06:16,320 Speaker 1: isn't one slice of turkey? Vegans? These are the voices 80 00:06:16,360 --> 00:06:19,560 Speaker 1: of some nice strangers who we interviewed while they were 81 00:06:19,600 --> 00:06:23,560 Speaker 1: shopping at a Whole Foods in Brooklyn, and there are 82 00:06:23,680 --> 00:06:30,600 Speaker 1: pretty good representation of well all of us. Everyone's at 83 00:06:30,680 --> 00:06:34,600 Speaker 1: least heard of a calorie, and for many of us, 84 00:06:34,880 --> 00:06:38,599 Speaker 1: they actually play a pretty big role in our decisions 85 00:06:38,640 --> 00:06:45,240 Speaker 1: about food. Calories have this incredible power over us. We're 86 00:06:45,520 --> 00:06:51,200 Speaker 1: obsessed with calories because we're obsessed with being thin, but 87 00:06:51,440 --> 00:06:55,040 Speaker 1: most of us have no idea what a calorie really 88 00:06:55,360 --> 00:07:01,480 Speaker 1: is or how they're calculated. And here's the thing. People 89 00:07:01,560 --> 00:07:05,400 Speaker 1: like to say a calorie is a calorie, but the 90 00:07:05,520 --> 00:07:10,800 Speaker 1: calorie isn't actually that straightforward. The number of calories in 91 00:07:10,840 --> 00:07:14,720 Speaker 1: a food can change depending on how we prepare it 92 00:07:15,120 --> 00:07:19,559 Speaker 1: and who's eating it. Calorie counts on foods can even 93 00:07:19,640 --> 00:07:25,880 Speaker 1: sometimes be wrong, like our almond from earlier. Scientists are 94 00:07:25,920 --> 00:07:29,960 Speaker 1: still to this day figuring out the best way to 95 00:07:30,080 --> 00:07:34,280 Speaker 1: measure how much energy the food that we eat has. 96 00:07:35,960 --> 00:07:40,120 Speaker 1: It's not just calories. Calories are the start of everything. 97 00:07:40,320 --> 00:07:44,400 Speaker 1: We still don't know about gaining and losing weight and 98 00:07:44,440 --> 00:07:48,760 Speaker 1: what weight has to do with being healthy anyway. But 99 00:07:48,880 --> 00:07:52,120 Speaker 1: that hasn't stopped people from telling you exactly how to 100 00:07:52,240 --> 00:07:56,760 Speaker 1: finally drop that last ten pounds or bragging that they 101 00:07:56,800 --> 00:08:01,160 Speaker 1: still fit into their high school genes or doctors from 102 00:08:01,200 --> 00:08:06,080 Speaker 1: telling you to lose weight. It also hasn't sat people 103 00:08:06,280 --> 00:08:10,880 Speaker 1: from making tons of money off of totally unscientific advice. 104 00:08:12,120 --> 00:08:16,600 Speaker 1: I'm am a court healthcare reporter for Bloomberg News. This 105 00:08:16,800 --> 00:08:21,960 Speaker 1: is Losing It a podcast from Prognosis. We've been trained 106 00:08:22,080 --> 00:08:26,240 Speaker 1: to think of dieting as a weight loss solution, but 107 00:08:26,320 --> 00:08:31,320 Speaker 1: a lot of the science actually suggests the opposite. Dieting 108 00:08:31,360 --> 00:08:34,160 Speaker 1: may work in the beginning to bring that number down 109 00:08:34,400 --> 00:08:38,240 Speaker 1: on the scale, but as the weeks and months turn 110 00:08:38,320 --> 00:08:43,200 Speaker 1: into years, the reality is that people usually don't keep 111 00:08:43,240 --> 00:08:47,520 Speaker 1: the weight off. This series is about how and why 112 00:08:47,840 --> 00:08:51,880 Speaker 1: we've been going about weight loss all wrong, and whether 113 00:08:51,920 --> 00:08:54,240 Speaker 1: we should even be trying to lose weight in the 114 00:08:54,280 --> 00:08:57,840 Speaker 1: first place. I'm also going to look for a better 115 00:08:57,880 --> 00:09:03,520 Speaker 1: solution for us away out of this whole mess. But first, 116 00:09:03,840 --> 00:09:22,640 Speaker 1: let's talk some more about the humble calorie. Let's go 117 00:09:22,760 --> 00:09:25,320 Speaker 1: back in time to when the calorie as we know 118 00:09:25,480 --> 00:09:30,199 Speaker 1: it was born. Calories got popularized in the late nineteenth 119 00:09:30,240 --> 00:09:35,120 Speaker 1: century by a guy named Wilbur olin Atwater. Wilbur was 120 00:09:35,200 --> 00:09:39,480 Speaker 1: a chemistry professor at Wesleyan University who also worked for 121 00:09:39,520 --> 00:09:42,920 Speaker 1: the U S d A. He's actually considered the father 122 00:09:43,160 --> 00:09:49,560 Speaker 1: of nutritional science in the US. Years earlier, European scientists 123 00:09:49,559 --> 00:09:52,800 Speaker 1: had come up with the idea of using calories to 124 00:09:52,880 --> 00:09:59,400 Speaker 1: measure energy. Remember, calories are a unit of energy. Scientists 125 00:09:59,480 --> 00:10:04,120 Speaker 1: began using them to talk about heat powering machines like 126 00:10:04,240 --> 00:10:16,240 Speaker 1: steam engines. Later they started measuring calories in food. Wilbur 127 00:10:16,440 --> 00:10:19,600 Speaker 1: was drawn to this new way of thinking and got 128 00:10:19,640 --> 00:10:23,400 Speaker 1: really serious about figuring out how much energy was in 129 00:10:23,440 --> 00:10:29,319 Speaker 1: different foods. Wilbur was also worried about people over eating. 130 00:10:30,120 --> 00:10:33,600 Speaker 1: He wanted to know how much food people really needed. 131 00:10:34,559 --> 00:10:37,880 Speaker 1: The calorie looked like a great way to do just that, 132 00:10:39,120 --> 00:10:42,040 Speaker 1: so he tries to get the word out. He also 133 00:10:42,160 --> 00:10:46,000 Speaker 1: came up with a formula for calculating the caloric value 134 00:10:46,080 --> 00:10:50,439 Speaker 1: of food based on how much of it is fat, protein, 135 00:10:50,720 --> 00:10:55,800 Speaker 1: and carbohydrates. That's actually how most calorie counts on foods 136 00:10:55,920 --> 00:11:00,720 Speaker 1: get calculated today. The bond calorimeter we used earlier to 137 00:11:00,800 --> 00:11:04,319 Speaker 1: blow up my almond is a more old school method. 138 00:11:10,240 --> 00:11:13,200 Speaker 1: The calorie is an attractive measure because it is a 139 00:11:13,240 --> 00:11:16,680 Speaker 1: simplified number in which you can sort of put in 140 00:11:16,720 --> 00:11:19,640 Speaker 1: front of an item of food. This is Giles Yo 141 00:11:20,280 --> 00:11:23,600 Speaker 1: scientist with the University of Cambridge, and people think the 142 00:11:23,679 --> 00:11:26,840 Speaker 1: higher the number the worst of food. In very but simplistically, 143 00:11:27,080 --> 00:11:29,559 Speaker 1: in the environment, the lower number the better, the food, 144 00:11:29,600 --> 00:11:32,720 Speaker 1: healthier it is for you. But that is not true. 145 00:11:33,080 --> 00:11:36,680 Speaker 1: Giles is not a fan of the calorie. He actually 146 00:11:36,760 --> 00:11:40,920 Speaker 1: wrote a book with a pretty blunt title, why Calories 147 00:11:40,960 --> 00:11:46,480 Speaker 1: Don't Count. And about a decade ago, scientists at the 148 00:11:46,600 --> 00:11:51,079 Speaker 1: U s d A also start asking big fundamental questions 149 00:11:51,160 --> 00:11:57,240 Speaker 1: about calories. Their names were David Bear and Janet Navatni, 150 00:11:58,400 --> 00:12:03,880 Speaker 1: and they became interested in nuts, specifically. Yes, we're going 151 00:12:03,920 --> 00:12:09,199 Speaker 1: to talk more about nuts in this episode. Anyway, they 152 00:12:09,280 --> 00:12:13,400 Speaker 1: noticed that in some studies where people were fed nuts, 153 00:12:13,600 --> 00:12:19,960 Speaker 1: their bodies weren't fully breaking the nuts down. That's the 154 00:12:20,000 --> 00:12:25,480 Speaker 1: politest way of putting in. What we started to think 155 00:12:25,520 --> 00:12:29,079 Speaker 1: about was if the fat isn't being completely digested this 156 00:12:29,160 --> 00:12:32,079 Speaker 1: is David, and it's coming out in the waste and 157 00:12:32,120 --> 00:12:36,640 Speaker 1: the faces, then the calories from the fat aren't being 158 00:12:36,679 --> 00:12:40,680 Speaker 1: completely absorbed as well. And it made us wonder whether 159 00:12:41,080 --> 00:12:45,920 Speaker 1: we were getting accurate calorie values for tree nuts. So 160 00:12:46,000 --> 00:12:49,400 Speaker 1: David and Janet put this theory to the test. They 161 00:12:49,440 --> 00:12:55,120 Speaker 1: did a series of studies looking at almonds, pistachios, cashews, 162 00:12:55,160 --> 00:12:59,400 Speaker 1: and walnuts, and it turned out their hunch was right. 163 00:13:00,840 --> 00:13:04,600 Speaker 1: The typical calorie counts the numbers listed on labels at 164 00:13:04,600 --> 00:13:09,640 Speaker 1: food stores were too high for those nuts. The fat, 165 00:13:10,280 --> 00:13:14,520 Speaker 1: the stuff that makes nuts so high calorie, wasn't being 166 00:13:14,760 --> 00:13:19,959 Speaker 1: fully digested. The scientists were able to see this right 167 00:13:20,480 --> 00:13:26,320 Speaker 1: in people's poop, and like David said, if people weren't 168 00:13:26,360 --> 00:13:32,400 Speaker 1: digesting all that fat, they also weren't absorbing the calories 169 00:13:32,480 --> 00:13:36,479 Speaker 1: from that fat. The nuts turned out to have anywhere 170 00:13:36,559 --> 00:13:43,000 Speaker 1: between five and fewer calories than their nutrition label set, 171 00:13:44,040 --> 00:13:48,920 Speaker 1: and the nuts with the biggest difference almonds, like the 172 00:13:48,960 --> 00:13:53,120 Speaker 1: one we blew up in the lab. Nuts, like all 173 00:13:53,280 --> 00:13:57,520 Speaker 1: plant material, have a cell wall, and that's where we 174 00:13:57,600 --> 00:14:03,160 Speaker 1: find the fiber that's also resistant to digestion. We can 175 00:14:03,160 --> 00:14:08,319 Speaker 1: ferment it and break it down, but plant cells are 176 00:14:08,360 --> 00:14:11,840 Speaker 1: surrounded by the cell wall, and until you can open 177 00:14:11,920 --> 00:14:15,280 Speaker 1: up that cell wall, you can't get to what's inside 178 00:14:15,600 --> 00:14:20,680 Speaker 1: the plant cell. In the case of nuts, they're relatively 179 00:14:20,760 --> 00:14:23,000 Speaker 1: high in fat, so there's a lot of energy stored 180 00:14:23,040 --> 00:14:27,640 Speaker 1: within those cells. With whole nuts, that means unless you're 181 00:14:27,720 --> 00:14:35,440 Speaker 1: a really thorough chew er, you're probably pooping a lot 182 00:14:35,480 --> 00:14:44,880 Speaker 1: of fat out and that means fewer calories. So in short, 183 00:14:45,840 --> 00:14:50,240 Speaker 1: nutritional labels have been telling us for years that a 184 00:14:50,280 --> 00:14:54,840 Speaker 1: bunch of different kinds of nuts are more caloric than 185 00:14:54,880 --> 00:14:59,160 Speaker 1: they actually are, and that could be the case for 186 00:14:59,280 --> 00:15:05,080 Speaker 1: other food too. We've been trained to take calorie counts 187 00:15:05,120 --> 00:15:10,320 Speaker 1: on food incredibly seriously. We count our calories so we 188 00:15:10,400 --> 00:15:13,960 Speaker 1: don't eat too many. We we food to make sure 189 00:15:13,960 --> 00:15:18,240 Speaker 1: we're counting exactly how many calories were eating, or we 190 00:15:18,360 --> 00:15:23,000 Speaker 1: buy prepackaged food because those numbers seem like they're more accurate. 191 00:15:24,160 --> 00:15:29,040 Speaker 1: But as I dug into this all of that, it 192 00:15:29,160 --> 00:15:33,640 Speaker 1: started to seem like a giant waste of time and effort. 193 00:15:36,440 --> 00:15:41,760 Speaker 1: Wilbolan Atwater intended calories to be a tool for making 194 00:15:41,840 --> 00:15:47,240 Speaker 1: better decisions about how to fuel ourselves. Instead, we've wound 195 00:15:47,280 --> 00:15:50,800 Speaker 1: up in this world where somehow a hundred calories of 196 00:15:50,880 --> 00:15:55,360 Speaker 1: nuts seems equivalent to a hundred calorie pack of chips. 197 00:15:56,480 --> 00:16:00,520 Speaker 1: We're focusing on the number over the quality of food, 198 00:16:00,720 --> 00:16:04,080 Speaker 1: and we're also focusing on the number way too much. 199 00:16:05,000 --> 00:16:08,960 Speaker 1: We've taken it way too far. Somewhere along the way, 200 00:16:09,200 --> 00:16:12,880 Speaker 1: calories went from a guide to navigating food to some 201 00:16:12,960 --> 00:16:18,360 Speaker 1: sort of holy infallible thing, and in the process they've 202 00:16:18,560 --> 00:16:24,440 Speaker 1: also kind of become misinformation. These issues with calories go 203 00:16:24,840 --> 00:16:31,200 Speaker 1: way beyond nuts. Processing food, including by cooking, it also 204 00:16:31,320 --> 00:16:37,320 Speaker 1: changes the amount of calories we get from it. Why well, 205 00:16:37,480 --> 00:16:42,640 Speaker 1: For one, digestion is work and how hard you are 206 00:16:42,680 --> 00:16:48,040 Speaker 1: working affects the end calorie count of a food. Processing 207 00:16:48,240 --> 00:16:52,280 Speaker 1: or cooking food makes for less work for your body. 208 00:16:52,320 --> 00:16:54,200 Speaker 1: Is it a carrot, Is it a steak? Is it 209 00:16:54,200 --> 00:16:57,440 Speaker 1: a donut? That our body has to look to differing 210 00:16:57,600 --> 00:17:01,600 Speaker 1: degrees hard or not as hard to extract the calories, 211 00:17:01,640 --> 00:17:04,040 Speaker 1: and this cost energy And so therefore you have to 212 00:17:04,080 --> 00:17:06,719 Speaker 1: take this into account when you're try and account the 213 00:17:06,760 --> 00:17:09,120 Speaker 1: calories within the food. It's your body has to work 214 00:17:09,160 --> 00:17:11,480 Speaker 1: a hell of a lot harder to put out calories 215 00:17:11,480 --> 00:17:13,719 Speaker 1: from a carrot than it needs to from a donut. 216 00:17:14,920 --> 00:17:18,320 Speaker 1: The calories and a food can even depend on who 217 00:17:18,440 --> 00:17:22,399 Speaker 1: is eating it. If you and I ate the same sandwich, 218 00:17:23,080 --> 00:17:27,240 Speaker 1: we might get different amounts of energy from it. That 219 00:17:27,280 --> 00:17:31,080 Speaker 1: has to do with how different bodies processed food differently 220 00:17:31,960 --> 00:17:37,080 Speaker 1: because of genetics and factors like the gut microbiome. So 221 00:17:37,280 --> 00:17:41,000 Speaker 1: even though nutrition labels make it seem like calories are 222 00:17:41,040 --> 00:17:47,159 Speaker 1: a fixed value. They actually aren't. Calorie counts on food 223 00:17:47,520 --> 00:17:52,560 Speaker 1: are misleading at best, and food companies are playing their 224 00:17:52,560 --> 00:17:57,400 Speaker 1: own games. Okay, so a serving as q cups, which 225 00:17:57,440 --> 00:18:02,040 Speaker 1: is decent. It's there's there's of it allegedly seven servings 226 00:18:02,040 --> 00:18:04,560 Speaker 1: in this spect a hundred and forty calories per serving 227 00:18:04,640 --> 00:18:08,240 Speaker 1: and seventy for a cup. Okay, So is this food 228 00:18:08,280 --> 00:18:11,439 Speaker 1: good or bad for you? I have no idea. That 229 00:18:11,640 --> 00:18:14,840 Speaker 1: was me and the editor of this podcast, Christin V. Brown. 230 00:18:15,720 --> 00:18:18,480 Speaker 1: We're back at that Whole Foods in Brooklyn where we 231 00:18:18,560 --> 00:18:22,600 Speaker 1: interviewed people about calories. We wanted to check out calor 232 00:18:22,720 --> 00:18:26,160 Speaker 1: counts in the wild to get a sense of how 233 00:18:26,200 --> 00:18:31,119 Speaker 1: helpful this tool for evaluating food really is. One of 234 00:18:31,160 --> 00:18:33,600 Speaker 1: the things we looked at was a bag of Musely, 235 00:18:34,119 --> 00:18:38,040 Speaker 1: a quarter cop as a hundred and forty calories. You know, Musely, 236 00:18:38,840 --> 00:18:42,200 Speaker 1: the breakfast cereal that's kind of like granola. So that's 237 00:18:42,240 --> 00:18:47,000 Speaker 1: the same as our thirteen potato chips and our popcorn? Right? Yeah? 238 00:18:48,359 --> 00:18:51,160 Speaker 1: Why is a hundred and forty the magic number? Most 239 00:18:51,200 --> 00:18:54,800 Speaker 1: foods we looked at were around hundred and forty calories 240 00:18:54,880 --> 00:18:59,520 Speaker 1: per serving and hundred and forty doesn't sound like that 241 00:18:59,680 --> 00:19:02,560 Speaker 1: many calories. Feel like everything has had the same amount 242 00:19:02,600 --> 00:19:06,399 Speaker 1: of calori. See also a hundred and sixty is anyone 243 00:19:06,400 --> 00:19:08,960 Speaker 1: going to a serving size with more than two hundred calories? 244 00:19:09,800 --> 00:19:14,040 Speaker 1: According to the Food and Drug Administration, a serving size 245 00:19:14,359 --> 00:19:19,760 Speaker 1: isn't a recommendation, it's actually how much people usually eat 246 00:19:19,920 --> 00:19:24,400 Speaker 1: or drink that product. So when you see thirteen potato 247 00:19:24,520 --> 00:19:28,520 Speaker 1: chips is a serving size that's supposed to be how 248 00:19:28,560 --> 00:19:35,080 Speaker 1: many potato chips people eat in a sitting. Potato chips, Yeah, right. 249 00:19:36,160 --> 00:19:39,200 Speaker 1: And don't even get me started on how many servings 250 00:19:39,200 --> 00:19:43,960 Speaker 1: are in a container. Often you buy something small that's 251 00:19:43,960 --> 00:19:48,119 Speaker 1: obviously meant to be a single serving, and yet somehow 252 00:19:48,240 --> 00:19:53,159 Speaker 1: the label claims it's two or three or even four servings. 253 00:19:54,600 --> 00:19:58,400 Speaker 1: The more servings in a container, the fewer calories companies 254 00:19:58,480 --> 00:20:01,399 Speaker 1: have to list on the label, and the better it 255 00:20:01,400 --> 00:20:04,960 Speaker 1: looks when you compare it to another food. You're just 256 00:20:05,040 --> 00:20:07,800 Speaker 1: relying on calories. You would say, okay, I could have 257 00:20:07,880 --> 00:20:10,080 Speaker 1: popcorn for breakfast, or I could add usely and it 258 00:20:10,080 --> 00:20:11,960 Speaker 1: would be the same amount of calories. And so why 259 00:20:12,000 --> 00:20:14,399 Speaker 1: should I choose the thing that seems kind of gross 260 00:20:14,400 --> 00:20:18,800 Speaker 1: and healthy? Our field trip to whole Foods left me 261 00:20:18,880 --> 00:20:25,520 Speaker 1: wondering are calories fundamentally broken. I'm pretty much leaning yes 262 00:20:25,960 --> 00:20:29,560 Speaker 1: at this point, but many of the experts I spoke 263 00:20:29,640 --> 00:20:34,440 Speaker 1: with said they're working to improve calorie counts, not get 264 00:20:34,520 --> 00:20:40,760 Speaker 1: rid of them. Here's their argument. Sure, calories aren't perfect, 265 00:20:41,359 --> 00:20:47,040 Speaker 1: but they're essentially accurate, if not precisely. So they give 266 00:20:47,119 --> 00:20:50,760 Speaker 1: you a number you can compare with other foods, and 267 00:20:50,880 --> 00:20:54,920 Speaker 1: that can help you decide whether to have, say a pizza, 268 00:20:55,480 --> 00:21:00,199 Speaker 1: or a big salad for dinner. Here's Rachel Carmody, an 269 00:21:00,200 --> 00:21:05,560 Speaker 1: assistant professor of human evolutionary biology at Harvard University, saying, 270 00:21:06,000 --> 00:21:08,399 Speaker 1: you know, these food labels have been horribly wrong, and 271 00:21:08,440 --> 00:21:10,920 Speaker 1: we're just going to now revamp them all, which could 272 00:21:11,040 --> 00:21:13,800 Speaker 1: lead to a lot of confusion. So I think this 273 00:21:13,880 --> 00:21:16,280 Speaker 1: has to be done responsibly. We're trying to make the 274 00:21:16,280 --> 00:21:19,880 Speaker 1: tool more useful. The problem with this, though, is that 275 00:21:20,000 --> 00:21:23,679 Speaker 1: we all know the salad is the healthier choice for dinner, 276 00:21:24,320 --> 00:21:30,360 Speaker 1: not pizza. Sadly, people still use calorie counts to make 277 00:21:30,440 --> 00:21:35,040 Speaker 1: decisions about what they buy and what they eat. We 278 00:21:35,080 --> 00:21:39,000 Speaker 1: want to believe the calorie is this highly accurate measure, 279 00:21:39,760 --> 00:21:44,520 Speaker 1: down to a single calorie or two food labels lead 280 00:21:44,640 --> 00:21:49,479 Speaker 1: us to believe the same, but calories really shouldn't be 281 00:21:49,600 --> 00:21:54,119 Speaker 1: used like that. Calories give us the illusion of control 282 00:21:54,320 --> 00:21:58,760 Speaker 1: over diet and weight, but it's just that an illusion. 283 00:22:00,080 --> 00:22:04,800 Speaker 1: Giles Yo, the University of Cambridge researcher, who is anti calorie, 284 00:22:05,040 --> 00:22:08,040 Speaker 1: says it would be better instead to communicate a few 285 00:22:08,160 --> 00:22:13,440 Speaker 1: key measures of nutritional value, specifically the amount of fiber, 286 00:22:13,840 --> 00:22:18,280 Speaker 1: protein added, sugar and fat in the food. My argument 287 00:22:18,520 --> 00:22:21,919 Speaker 1: is to move away from the calorie per se, but 288 00:22:22,040 --> 00:22:26,399 Speaker 1: actually to consider the quality of the food, and I 289 00:22:26,440 --> 00:22:29,520 Speaker 1: think that is far more important. Now. It happens to 290 00:22:29,560 --> 00:22:33,119 Speaker 1: be related to the calorie, but the calorie is a 291 00:22:33,160 --> 00:22:37,440 Speaker 1: blunt tool in terms of trying to measure the quality 292 00:22:37,480 --> 00:22:39,280 Speaker 1: of a of any given food you're trying to eat. 293 00:22:40,000 --> 00:22:44,000 Speaker 1: When Giles talks about high quality foods, he means those 294 00:22:44,080 --> 00:22:48,840 Speaker 1: that have more protein and fiber, like beans or chicken 295 00:22:49,800 --> 00:22:54,280 Speaker 1: nuts count two. His point is a good one. Calories 296 00:22:54,280 --> 00:22:58,520 Speaker 1: can be deceptive. A can of coca cola and a 297 00:22:58,600 --> 00:23:04,000 Speaker 1: pint of strawberries both have similar numbers of calories, but 298 00:23:04,119 --> 00:23:10,280 Speaker 1: they definitely do not have similar nutritional values. It's easy, though, 299 00:23:10,359 --> 00:23:14,440 Speaker 1: to think that low calorie means healthy. We talk about 300 00:23:14,440 --> 00:23:18,480 Speaker 1: weight loss in the same way too, Like anyone who 301 00:23:18,520 --> 00:23:21,760 Speaker 1: goes on a diet and loses fifteen pounds is going 302 00:23:21,800 --> 00:23:25,399 Speaker 1: to be in better shape. But if I went on 303 00:23:25,520 --> 00:23:29,240 Speaker 1: an all coca cola diet and lost weight, would I 304 00:23:29,280 --> 00:23:34,359 Speaker 1: be healthier? That's why we shouldn't make weight loss equivalent 305 00:23:34,520 --> 00:23:38,600 Speaker 1: with good health. Something will get into leader in the series. 306 00:23:40,640 --> 00:23:44,600 Speaker 1: We also now know that calorie counts on labels don't 307 00:23:44,640 --> 00:23:48,959 Speaker 1: actually tell us how many calories of food has because 308 00:23:49,119 --> 00:23:52,359 Speaker 1: how you prepare food and how you digest it and 309 00:23:52,440 --> 00:23:56,560 Speaker 1: a lot of other things can change the number. And 310 00:23:56,680 --> 00:24:01,479 Speaker 1: yet calories are still being treated as the truth. There 311 00:24:01,480 --> 00:24:05,280 Speaker 1: are labels as fact when they probably need at least 312 00:24:05,320 --> 00:24:09,480 Speaker 1: an asterisk. Diets are being sold to people based on 313 00:24:09,520 --> 00:24:13,960 Speaker 1: the science behind these numbers. That's a global industry worth 314 00:24:14,040 --> 00:24:18,239 Speaker 1: a hundred and ninety two billion dollars a year. And 315 00:24:18,320 --> 00:24:23,000 Speaker 1: people are relying on calories deciding whether they buy or 316 00:24:23,119 --> 00:24:28,960 Speaker 1: eat food because of them. They're meticulously counting them, measuring 317 00:24:29,000 --> 00:24:33,240 Speaker 1: their foods to make sure that no calorie goes unaccounted for. 318 00:24:36,280 --> 00:24:38,760 Speaker 1: The crucial moment for me was when you know, we 319 00:24:38,840 --> 00:24:42,320 Speaker 1: had a holiday event at work and I didn't like 320 00:24:42,440 --> 00:24:45,199 Speaker 1: my photos I didn't like it, and I was like, 321 00:24:45,320 --> 00:24:48,119 Speaker 1: I really have to make change for myself because I 322 00:24:48,160 --> 00:24:50,879 Speaker 1: didn't like the way. You know, I look, this is 323 00:24:50,960 --> 00:24:55,320 Speaker 1: Danny Cologne. She's talking about photos from a Christmas luncheon 324 00:24:55,480 --> 00:24:58,760 Speaker 1: her company through in two thousand and six. I thought 325 00:24:58,800 --> 00:25:02,119 Speaker 1: myself on the thicker side and you know, I have 326 00:25:02,200 --> 00:25:04,639 Speaker 1: my little double chin, and I didn't like it. It 327 00:25:04,720 --> 00:25:07,480 Speaker 1: was just like, I don't like seeing myself like that. 328 00:25:07,520 --> 00:25:10,239 Speaker 1: I had never gotten to that that point before, and 329 00:25:10,280 --> 00:25:13,159 Speaker 1: that was the turning point for me. Deeany says she 330 00:25:13,280 --> 00:25:17,399 Speaker 1: first started battling the scale about twenty years ago after 331 00:25:17,480 --> 00:25:21,600 Speaker 1: having her second child. She's now forty three and a 332 00:25:21,640 --> 00:25:24,560 Speaker 1: mother of five. I was never a big girl, but 333 00:25:24,760 --> 00:25:26,560 Speaker 1: I had gained a little bit and I was always 334 00:25:26,560 --> 00:25:29,600 Speaker 1: trying to lose it, you know what I mean. And 335 00:25:29,640 --> 00:25:31,919 Speaker 1: as when I had my third child, so that was 336 00:25:31,960 --> 00:25:34,760 Speaker 1: a little bit. You know, then it just starts adding 337 00:25:34,840 --> 00:25:37,840 Speaker 1: up and you're trying. But it's you know, as the 338 00:25:37,840 --> 00:25:40,840 Speaker 1: older you get, the harder it is. Plus I was 339 00:25:41,240 --> 00:25:45,359 Speaker 1: a full time employee, plus I was at home. I 340 00:25:45,400 --> 00:25:47,359 Speaker 1: had to a sense to the kids and for me 341 00:25:47,440 --> 00:25:49,760 Speaker 1: to the thought of even having to make two wheels 342 00:25:50,160 --> 00:25:53,760 Speaker 1: as in a diet meal for herself and another meal 343 00:25:53,960 --> 00:25:57,240 Speaker 1: for her family was very very hard on me. So 344 00:25:57,560 --> 00:25:59,840 Speaker 1: it was just something that was always on the back burner. 345 00:26:00,119 --> 00:26:03,399 Speaker 1: At the time, Danny was working as a project coordinator 346 00:26:03,560 --> 00:26:07,560 Speaker 1: in Tampa, Florida. She now lives in Puerto Rico. You 347 00:26:07,600 --> 00:26:09,600 Speaker 1: want to get on this weight lost journey, but there's 348 00:26:09,680 --> 00:26:13,120 Speaker 1: so much out there an aesthetic. I need my carbs, 349 00:26:14,359 --> 00:26:16,680 Speaker 1: so it was very hard to reay, be like, I 350 00:26:16,720 --> 00:26:19,639 Speaker 1: can't just eat need the vegetables, and it's hard to 351 00:26:19,680 --> 00:26:22,720 Speaker 1: cut out a whole book group. So to take out 352 00:26:22,720 --> 00:26:27,080 Speaker 1: that completely, Yeah, that wasn't gonna work for my household. 353 00:26:28,280 --> 00:26:32,480 Speaker 1: Danny tries out a couple of different programs. Some even 354 00:26:32,640 --> 00:26:36,639 Speaker 1: helped her lose weight, but they all had some kind 355 00:26:36,760 --> 00:26:42,360 Speaker 1: of downside. The costs, in particular, were an obstacle for her. 356 00:26:43,480 --> 00:26:47,840 Speaker 1: One program cost five dollars just to sign up. I mean, 357 00:26:47,840 --> 00:26:50,080 Speaker 1: every time you go to a weight loss program, you're 358 00:26:50,119 --> 00:26:53,159 Speaker 1: paying money. And I was like, Okay, maybe I'm ready. 359 00:26:53,200 --> 00:26:55,640 Speaker 1: Now I got the tools that I need, and maybe 360 00:26:55,720 --> 00:26:58,520 Speaker 1: i'll I can do this on my own and I 361 00:26:58,520 --> 00:27:01,360 Speaker 1: don't have to invest in that money. Danny knew from 362 00:27:01,359 --> 00:27:05,159 Speaker 1: her previous experiences with weight loss programs that tracking the 363 00:27:05,200 --> 00:27:09,919 Speaker 1: food she eats really helps, so she starts calorie counting 364 00:27:10,280 --> 00:27:13,840 Speaker 1: with the help of some free online tools. There are 365 00:27:13,880 --> 00:27:17,240 Speaker 1: all these random calculators out there that you can use 366 00:27:17,400 --> 00:27:21,400 Speaker 1: to decide how many calories to eat based on how 367 00:27:21,480 --> 00:27:25,360 Speaker 1: much weight you want to lose. Danny uses one and 368 00:27:25,520 --> 00:27:30,160 Speaker 1: decides she needs to eat less than calories a day. 369 00:27:30,640 --> 00:27:36,560 Speaker 1: This time, the diet starts working almost immediately. She loses 370 00:27:36,680 --> 00:27:42,200 Speaker 1: twelve pounds in twelve weeks. The program is simple, eat 371 00:27:42,280 --> 00:27:46,400 Speaker 1: less and move more. It's free, and Danny can see 372 00:27:46,480 --> 00:27:50,800 Speaker 1: the results. I'm like more of a harder to lose weight. 373 00:27:50,880 --> 00:27:54,560 Speaker 1: Maybe I have a flower metabolism. But once I started 374 00:27:54,640 --> 00:27:58,440 Speaker 1: seeing that my clothes was, you know, sitting a little 375 00:27:58,440 --> 00:28:01,480 Speaker 1: bit more loose, and I started getting on the scale 376 00:28:02,040 --> 00:28:05,399 Speaker 1: and the numbers were going little by little, I was 377 00:28:05,440 --> 00:28:08,720 Speaker 1: like very, very motivated, and to think, oh my gosh, 378 00:28:08,720 --> 00:28:12,640 Speaker 1: I'm being successful was just amazing. So it just makes 379 00:28:12,680 --> 00:28:16,879 Speaker 1: you strive for more. Danny is currently allowing herself about 380 00:28:16,960 --> 00:28:23,040 Speaker 1: twelve hundred calories each day. That's pretty low. A woman 381 00:28:23,160 --> 00:28:27,960 Speaker 1: her age really needs around two thousand calories. But for 382 00:28:28,080 --> 00:28:32,720 Speaker 1: what it's worth, government guidelines say most women can safely 383 00:28:32,840 --> 00:28:37,800 Speaker 1: lose weight eating twelve hundred to fift hundred calories a day. 384 00:28:38,000 --> 00:28:41,280 Speaker 1: Danny uses this app called lose It, which keeps track 385 00:28:41,360 --> 00:28:44,959 Speaker 1: of her calorie budget. If she has a hundred calorie 386 00:28:45,000 --> 00:28:51,320 Speaker 1: cup of plane Cheerios, then she has eleven hundred left easy. 387 00:28:51,520 --> 00:28:54,480 Speaker 1: She also likes the flexibility. The good thing about calor 388 00:28:54,480 --> 00:28:58,120 Speaker 1: a counting is that you're not excluding any food groups 389 00:28:58,520 --> 00:29:01,680 Speaker 1: at all. Like let's say that Danny plans on having 390 00:29:01,800 --> 00:29:06,080 Speaker 1: salmon and potatoes for lunch, but it doesn't end up happening. 391 00:29:06,760 --> 00:29:10,000 Speaker 1: You just stand. You just put in your app. You know, hey, 392 00:29:10,040 --> 00:29:13,280 Speaker 1: I had a pizza, cheese, whatever, and that's it. Other 393 00:29:13,360 --> 00:29:17,200 Speaker 1: diets are more rigid. In other words, that's the good 394 00:29:17,240 --> 00:29:19,160 Speaker 1: thing about it is like people don't have to over 395 00:29:19,240 --> 00:29:23,480 Speaker 1: stress on oh my god, I've failed because I had 396 00:29:23,520 --> 00:29:26,600 Speaker 1: a slice of pizza. You can have your slice of pizza, 397 00:29:27,200 --> 00:29:30,400 Speaker 1: just you know that you wake this much amount of 398 00:29:30,440 --> 00:29:33,640 Speaker 1: kellys on that pizza, so have a smaller amount for 399 00:29:33,720 --> 00:29:40,240 Speaker 1: your dinner. Danny loses weight calorie counting until she doesn't. 400 00:29:41,280 --> 00:29:46,080 Speaker 1: It's hard to keep it up. Life happens. Her mom 401 00:29:46,160 --> 00:29:49,680 Speaker 1: gets sick and Danny travels to see her in the hospital, 402 00:29:50,600 --> 00:29:54,400 Speaker 1: where she's stressed and sad, and there's a lot of 403 00:29:54,520 --> 00:29:58,120 Speaker 1: fast food. One time, I want to be donald thinking, Okay, 404 00:29:58,160 --> 00:30:00,640 Speaker 1: what's the healthiest thing on the menu, And I thought, oh, 405 00:30:00,760 --> 00:30:04,920 Speaker 1: chicken nuggets. That's what I thought. Chicken nugget, chicken nuggets 406 00:30:04,920 --> 00:30:08,040 Speaker 1: of fries and you know so of diet soa, and 407 00:30:08,160 --> 00:30:11,640 Speaker 1: I thought that was the healthiest staying on the menu 408 00:30:11,800 --> 00:30:13,640 Speaker 1: at the moment because I'm looking at Okay, it's not 409 00:30:13,760 --> 00:30:16,640 Speaker 1: for it, it's not a burger. Let me just seek 410 00:30:16,640 --> 00:30:20,080 Speaker 1: a couple of nuggets. No, it was like a thousand 411 00:30:20,120 --> 00:30:25,560 Speaker 1: four until it. I was like most people have this experience. 412 00:30:26,440 --> 00:30:31,800 Speaker 1: Losing weight works until it doesn't. Several studies have shown 413 00:30:32,000 --> 00:30:36,760 Speaker 1: that many dieters will regain most or even all of 414 00:30:36,800 --> 00:30:42,200 Speaker 1: their lost weight. In some cases, they'll even gain more weight. 415 00:30:44,080 --> 00:30:48,640 Speaker 1: Between her mom's health issues and travel, Danie isn't calorie 416 00:30:48,640 --> 00:30:52,320 Speaker 1: counting as much. She ends up gaining back the weight 417 00:30:52,480 --> 00:30:57,240 Speaker 1: she lost. But Deanie is trying to calorie count again 418 00:30:57,960 --> 00:31:01,120 Speaker 1: and it's still a big fan of the approach. She 419 00:31:01,240 --> 00:31:04,800 Speaker 1: helps manage a Facebook group We're about twenty three thousand 420 00:31:04,880 --> 00:31:09,440 Speaker 1: people gathered to ask questions and trade tips. When her 421 00:31:09,520 --> 00:31:13,760 Speaker 1: daughter gained some weight, after having her first child, Danny 422 00:31:13,920 --> 00:31:18,880 Speaker 1: recommended calorie counting. Her daughter lost nearly twenty pounds in 423 00:31:18,920 --> 00:31:23,000 Speaker 1: a few months. When we talk, Danny runs me through 424 00:31:23,240 --> 00:31:28,040 Speaker 1: the caloric value of precisely everything she has eaten that day. 425 00:31:28,600 --> 00:31:31,360 Speaker 1: So today I haven't had lunch yet, so but this 426 00:31:31,480 --> 00:31:35,400 Speaker 1: morning I did have coffee. I had a Starbucks pumpkin 427 00:31:35,480 --> 00:31:39,520 Speaker 1: pie creamer and that was for a two hours. It's 428 00:31:39,520 --> 00:31:41,479 Speaker 1: a lot, but I'm gonna invite it a little bit, 429 00:31:41,480 --> 00:31:44,240 Speaker 1: a little. And then I had the rest was in coffee, 430 00:31:44,640 --> 00:31:48,680 Speaker 1: So coffee zero calories. So just on my coffee alone, 431 00:31:48,680 --> 00:31:52,440 Speaker 1: I had a hundred because of the creamer. It's mostly 432 00:31:52,480 --> 00:31:55,040 Speaker 1: the coin, it's all there. And then I had a 433 00:31:55,040 --> 00:31:58,120 Speaker 1: little bit stody like a little cookie study and that 434 00:31:58,240 --> 00:32:00,680 Speaker 1: set that was a hundred and thirty cows, So I 435 00:32:00,760 --> 00:32:04,480 Speaker 1: just counted a hundred dark We're on a zoom call 436 00:32:04,680 --> 00:32:07,560 Speaker 1: so I can actually see Danny's app and then right 437 00:32:07,600 --> 00:32:10,560 Speaker 1: here on the very top it shows it shows you 438 00:32:11,040 --> 00:32:15,240 Speaker 1: my actual budget and what I had, and it's subtracted. 439 00:32:15,640 --> 00:32:17,040 Speaker 1: So for the rest of the day, I have nine. 440 00:32:20,360 --> 00:32:22,960 Speaker 1: I asked Danny about the studies that have found calori 441 00:32:22,960 --> 00:32:27,440 Speaker 1: accounts may not be so accurate she doesn't seem too concerned. 442 00:32:28,400 --> 00:32:32,120 Speaker 1: Even if the numbers aren't exactly right. The scale tells 443 00:32:32,160 --> 00:32:35,400 Speaker 1: the truth at the end of the day. She also 444 00:32:35,440 --> 00:32:38,800 Speaker 1: tells me that since her mother's illness and all that travel, 445 00:32:39,640 --> 00:32:42,640 Speaker 1: she hasn't been as consistent with calorie counting as she 446 00:32:42,680 --> 00:32:45,960 Speaker 1: would like. She's a little mad at herself about it, 447 00:32:46,920 --> 00:32:49,880 Speaker 1: but she's more resolute than ever to stick to her 448 00:32:49,920 --> 00:32:53,760 Speaker 1: calorie goals and to lose more weight. I started getting 449 00:32:53,760 --> 00:32:56,479 Speaker 1: back on track, but then there was days work, So 450 00:32:56,520 --> 00:32:59,240 Speaker 1: I would track for about a week consistently, and then 451 00:32:59,280 --> 00:33:03,120 Speaker 1: mess up and then just and then try again, and 452 00:33:03,160 --> 00:33:05,440 Speaker 1: then just mess up and then try again. It's just 453 00:33:05,640 --> 00:33:09,600 Speaker 1: it's that since that point over, um, it's kind of 454 00:33:09,840 --> 00:33:12,800 Speaker 1: really hard for me to like consistently keep it up. 455 00:33:13,080 --> 00:33:16,120 Speaker 1: And the stakes are higher now. I just found out 456 00:33:16,200 --> 00:33:20,800 Speaker 1: that I have diabetes and it's in the starting stages 457 00:33:21,520 --> 00:33:25,240 Speaker 1: and high clipso and so I'm I've really started taking 458 00:33:25,240 --> 00:33:28,760 Speaker 1: the seriously. To me, it felt like Danny had been 459 00:33:28,880 --> 00:33:34,200 Speaker 1: misled by calories and weight loss in general. She'd used 460 00:33:34,200 --> 00:33:39,200 Speaker 1: calorie counting to lose twelve pounds several years ago, but 461 00:33:39,280 --> 00:33:42,640 Speaker 1: it hadn't been working very well for her since she 462 00:33:42,760 --> 00:33:47,160 Speaker 1: called calorie counting flexible, but it didn't really seem to 463 00:33:47,160 --> 00:33:52,440 Speaker 1: accommodate her actual life. Again, She's trying to eat twelve 464 00:33:52,640 --> 00:33:58,240 Speaker 1: dred calories a day, which is very restrictive. Danny likes 465 00:33:58,280 --> 00:34:01,840 Speaker 1: the precision that calorie counting seems to offer, but a 466 00:34:01,960 --> 00:34:06,000 Speaker 1: very precise method that's hard to stick to isn't very 467 00:34:06,040 --> 00:34:08,840 Speaker 1: precise at the end of the day. And Danny didn't 468 00:34:08,880 --> 00:34:13,280 Speaker 1: blame the system or even calories for the problems she'd had. 469 00:34:14,320 --> 00:34:19,399 Speaker 1: She blamed herself. So I'm thinking to myself, I really 470 00:34:19,400 --> 00:34:22,560 Speaker 1: have to start when I'm supposed to lose the weight, 471 00:34:22,840 --> 00:34:28,120 Speaker 1: to start feeling better and manage my health as best psyche. 472 00:34:28,880 --> 00:34:30,600 Speaker 1: And I know a lot of it has to do 473 00:34:30,680 --> 00:34:33,600 Speaker 1: with my insects. I'm not eating the white things. I'm 474 00:34:33,600 --> 00:34:41,480 Speaker 1: not want to feel good. Danny's story isn't unique. It 475 00:34:41,560 --> 00:34:45,600 Speaker 1: isn't even a modern story. Really, people have been marketing 476 00:34:45,880 --> 00:34:50,000 Speaker 1: super restrictive and even silly weight loss plans for a 477 00:34:50,040 --> 00:34:52,880 Speaker 1: long time. I mean that the classic story is that 478 00:34:53,200 --> 00:34:55,719 Speaker 1: until the late nineteenth century, if you were a little 479 00:34:55,719 --> 00:34:58,640 Speaker 1: bit plump, it was probably a sign a that you 480 00:34:58,680 --> 00:35:01,200 Speaker 1: were healthy because you had an of to eat and 481 00:35:01,320 --> 00:35:04,120 Speaker 1: be you were successful because you had enough to eat, 482 00:35:04,560 --> 00:35:06,880 Speaker 1: and that just begins to drop off and the fashion 483 00:35:06,960 --> 00:35:13,240 Speaker 1: begins to emphasize slenderness. Dieting in the truly modern sense 484 00:35:13,560 --> 00:35:17,600 Speaker 1: didn't take off until the nineteenth century or around the 485 00:35:17,600 --> 00:35:21,520 Speaker 1: time of the Industrial Revolution, and the real start of 486 00:35:21,600 --> 00:35:27,320 Speaker 1: diet history begins even further back than that. From chewing 487 00:35:27,320 --> 00:35:31,400 Speaker 1: your food a jillion times like Nancy Reagan to Keto 488 00:35:31,640 --> 00:35:34,759 Speaker 1: and scamm me weight loss pills, It turns out that 489 00:35:34,880 --> 00:35:40,120 Speaker 1: diet history definitely repeats itself. So Janette says that after 490 00:35:40,160 --> 00:35:43,120 Speaker 1: taking apple side of vinegar she felt less blown because 491 00:35:43,280 --> 00:35:45,560 Speaker 1: before and after on her and Michelle says she saw 492 00:35:45,560 --> 00:35:49,800 Speaker 1: a major improvement in her energy throughout the day. Fun fact, 493 00:35:50,520 --> 00:35:54,200 Speaker 1: the poet Lord Byron was super into vinegar as a 494 00:35:54,200 --> 00:35:58,640 Speaker 1: weight loss strategy too. Next time, on Losing It, we 495 00:35:58,719 --> 00:36:02,759 Speaker 1: take a trip back into time through diet history. First 496 00:36:02,800 --> 00:36:07,799 Speaker 1: stop Renaissance Italy. My physicians declared there was but one 497 00:36:07,920 --> 00:36:12,040 Speaker 1: remedy left for my eels. That remedy was the temperate 498 00:36:12,160 --> 00:36:17,719 Speaker 1: and orderly life. Losing It is written and reported by 499 00:36:17,800 --> 00:36:22,760 Speaker 1: me Emma Court and edited by Kristin V. Brown. Magnus 500 00:36:22,800 --> 00:36:27,440 Speaker 1: Hendrickson is our senior producer Stacy Wong our associate producer, 501 00:36:27,800 --> 00:36:31,880 Speaker 1: and Blake Maples is our audio engineer. Our theme was 502 00:36:31,960 --> 00:36:36,640 Speaker 1: composed and performed by Hannis Brown thanks to Francesco Leavie 503 00:36:36,840 --> 00:36:40,560 Speaker 1: and Tim Anette. Be sure to subscribe to Prognosis if 504 00:36:40,560 --> 00:36:44,080 Speaker 1: you haven't already, and if you like our show, please 505 00:36:44,239 --> 00:36:47,879 Speaker 1: leave us a review that helps others find out about it. 506 00:36:48,840 --> 00:36:51,120 Speaker 1: Thanks for listening, See you next time.