Weight loss is rarely linear…. 📉
Most people measure their fat loss progress by stepping on scales. This can create an all or nothing mentality and can impact not only your happiness but your behaviour. If the scales don’t go down when you’ve been ‘good’ then what’s the point? You may as well throw in the towel and enjoy that cake!
Weight loss is rarely linear. It’s normal for your weight to fluctuate on a day-to-day basis. There will be days where your scale weight goes up, just like there will be days where your weight will drop, and there will also be days (maybe even weeks) where your weight will stay exactly the same. Your weight can fluctuate up to 6kg during the day depending on what you eat and drink, and how you exercise. If you drink 2-3 litres of water a day that’s up to 3kg. Then how much do you pee, sweat and breathe out over the day? It’s impossible to measure. Our bodies are mainly water so changes in hydration cause significant weight fluctuations.
In addition a bowel full of food, a big meal the night before, fibrous or salty meals, and menstrual cycle hormone changes can all influence weight and cause greater daily fluctuations so real change can be hidden. Exercise can affect the scale both ways; if, after a workout, you’ve refuelled properly your muscles will be full of glycogen and water. On the other hand if you’ve sweated loads your weight will drop due to dehydration. Alcohol does the same; it’s a diuretic so will dehydrate you initially, but can cause cravings for salty foods leading to water retention.
For many of us, seeing that weight go up, despite ‘being good’, can make us give up. It’s vital to trust the process and think long term. The graph above is real client data. Look at how the weight fluctuates and look at the overall trend. By trusting the process and not giving up when the scales went up they’ve continued their weight loss over time.
We’re conditioned to focus on weight but instead try to use other measures e.g. items of clothing and how they fit, or cm measurements etc. If you must step on the scales then look at averages over time rather than daily variations and focus on long term trends.