Stress Fractures

stress. fractures, tibia, fibula

What’s up ? This is THE stephane ANDRE. With my training, I’m interested in biomechanics to avoid injuries. I read « Sport Medicine Media Guide » and I learned some good stuff.

A stress fracture is an overuse injury. Human body creates a new bone to replace a bone that has been broken due to the stress of everyday life. This process is done every day to keep the balance. Unfortunately, this balance can be disrupted because of excessive physical training. There are several factors that can prevent the body from creating enough bone and this make microcracking, called « fracture stress ».

The most common factor of fracture stress is an excessive increase in the intensitiy or frequency of physical activity without adequate rest period. Other factors are nutritional deficiencies, mechanical influences, lack of sleep, systemic factors (hormonal imbalance, etc.) and metabolic bone disorders.

There are case of development of eating disorders and/or amenorrhea (infrequent menstrual periods) for some female athletes who are preparing for a competition. These 2 conditions can create a decrease in estrogen that can decrease bone mineral density. This increase the risk of stress fractures.

Stress fractures are often seen in athletes (especially runners) or military recruiting. For an athlete, 1.6km run is 110 tons of force absorbed by the legs. Bones aren’t made to resist this force (energy) so it’s the muscles that have the function of absorbing shocks.

When the muscles get tired, they stop absorbing the forces and eveything transferred to the bones. Stress fractures occur in almost all bones but are more common in lower bone, expecially the tibia. Depending on the type of sport, there’re distinctive stress fractures such as the elbow in throwing sports, the ribs in golfing and rowing, the spine in gymnastics, the lower extremity in running activities and the foot in gymnastics and bascketball.

Diagnosis

stress, fracture, foot, metatarsal, 5th
stress, fracture, foot, x-rays, metatarsal,2nd

Stress fractures create pain in a limited area directly above the tip of the bone where the fracture occurred. The pain is raw because of physical activity and relived with rest. The sensitivity of the bones is the most obvious conclusion to the physical examination.

With regard to X-rays, this isn’t a tool that actually helps to diagnose an early stress fracture because the bone often looks normal and the microcracking aren’t visible. It’s difficult because after several weeks of rest, the bone begins to repair itself and shows a healing reaction or callus on X-rays.

An early stress fracture is usually confirmed by a bone scan or magnetic resonance imaging (MRI).

Treatment

Stress fractures are generally classified as low-risk (will not become a serious fracture) or high-risk (will become a serious fracture).

Low-risk stress fractures usually require a rest period of 1-6 weeks of limited weight bearing activity progressing to full weight bearing may be necessary. Return to physical activity should be a gratual process.

Low impact activities like swimming or biking are recommended to maintain cardiovascular condition when the pain is gone. When the patient can comfortably perform low impact activities for long, pain-free periods, the patient can begin high-impact activities.

High-risk stress fracture have the danger of becoming a complete fracture. For athletes suffering from chronic pain and having normal x-rays results, it’s recommanded to use a bone scan or MRI. High-risk stress fractures should be treated as traumatic fractures (with cast or surgery) because of complications.

Prevent

food, vitamin,d, carrot, papay, meat, ,egg, chees, broccoli, fish, sweet, potato, mango, pepperoni, apricot, peach, melon, avocado
calcium, food, almond, amarant, grain, aparagus, apricot, artichoke, baked, bean, haricot, blackberry, blackstrap, molasse, blackcurrant, bok, choy, brazil, nut, bread, wholemeal, brocolly, chickpeas, cinnamon, edamame, soya, fennel, kale, kidney, olive, orange, sesame, seed, milk, spring, green, tofu, swede, walnut, watercress

Here are tips developed by AAOS to help to prevent stress fractures :

  • When an athete does a new sport activity, it’s necessary to program progressive goals. For example on the 1st day, don’t run 8km but rather increase the distance gradually per week.
  • Cross-training => Alternate activities to achieve the same fitness goal helps to avoid stress fracture injuries. For example to achieve a cardiovascular goal, alternate cycling and running (cycling one day and riding the other day) is excellent. Adding strength training and doing flexibility exercises help improve performance.
  • Have and maintain a heathy diet with foods rich in calcium and vitamin D.
  • Use good equipment. Don’t use running shoes, gloves, etc, very old and very worn.
  • If during physical activity it start to swell or the pain starts, stop the activity right away. It’s essential to rest for a few days. If the pain continue, you should see an orthopedic surgeon.
  • It’s important to recognize early symptoms and treat them appropriately to return to the sport with a normal level of play.

Stats

  • Stress fractures occur less frequently in those of black African descent than in Caucasians, due to a generally higher BMD (bone mineral densitiy) in the former.
  • Women and highly active individuals are also at a higher risk, The incidence probably also increases with age due to age-related reductions in BMD.
  • Children may also be at risk because their bones have yet to reach full density and strength.
  • The female athlete triad also can put women at risk, as disordered eating and osteoporosis can cause the bones to be severely weakened.

Subscribe to my newsletter and share this article if you think it can help someone you know. Thank you.

-Steph

P.S. If you’re in Miami and you like Caribbean food, go to my cousin’s bistro to eat Haitian food, click here .

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Chi-Square Test With More Than 2 Categories

tableau chi square test

I have just enrolled in a Data Science course on Udemy  and I learned good stuff.

In this article, we will do a Chi-square test with more than 2 categories. We will use the A/B test « Country » which has 3 categories which corresponds to 3 countries : German, Spain and France. Select « Gender Actual » tab, make a copy with a right-click and select « Duplicate ».

tableau chi square test

Name the tab « Gender Actual (2) » by « Country Actual ».

tableau chi square test

In « Dimensions », move the variable « Geography » over « Gender » in « Columns » to replace « Gender » with « Geography ».

tableau chi square test

tableau chi square test

Here’s how to do an A/B statistical test when there are 3 categories. We’ll start with the classic method and then I’ll show you another way to do Chi-square test with any number of categories.

Let’s start with the classical method. In this case, there are 3 categories so we can’t use the online tool of the previous article. In the previous article we used an online tool with only 2 categories « Sample1 » and « Sample2 ». That’s why we’re going to use another online tool, click here  .

tableau chi square test

In this online tool, we can enter the values without using the total values. That is, we enter only the number of observations in each category. We simply need to enter the values that are on our A/B test. And I’m going to show you how to turn our A/B test into a table. In this way, it will be easier to enter the values in the online tool without making any mistakes.

Go to the « Show me » tool at the top right.

tableau chi square test

Click on « text tables »

tableau chi square test

tableau chi square test

Click on « Swap Rows ans Columns » button.

tableau chi square test

tableau chi square test

Cool, now you have a table arranged in exactly the same way as the online tool.

In the online tool, we will select 2 rows and 3 columns.

tableau chi square test

As we have 3 categories and 2 possible results, we enter our values exactly as in the table we just created on Tableau.

tableau chi square test

Perfect, our table is ready. You can click on the « Calculate » button.

tableau chi square test

tableau chi square test

As you can see, we observe the same thing as the other online tool. There is our indicator « p » value which is less than 5%. Which means there is a meaning.

tableau chi square test

This statistical significance means that these results are valid for the total number of the bank’s clients and not just for the sample of 10 000 clients. We observe similar differences with A/B test « Country » whose results are based solely on the sample of 10 000 clients. We can conclude that in the total number of the bank’s clients, it’s the clients in Germany who are more likely to leave the bank. This is how we do things cleanly.

You saw, this online tool limited by 5 by 5 tables so you can’t use this tool when you have 6 categories or more. But fortunately it’s possible to do Chi-square test with any number of categories. It’s a special method and for you to understand that, I’ll give you a theoretical explanation.

Here we have 3 countries : German, Spain and France.

tableau chi square test

What we’re trying to compare is the clients number leaving the bank in each of these countries.

tableau chi square test

With our basic A/B test based on a sample of 10 000 clients, we obtained 16% for France, 32% for Germany and 17% for Spain. Now the question is : « Do we observe the same results on the total clients number of the bank ? », it means : « In general, does the country have a significant effect on the clients number leaving bank ? ». Germany has the largest number of clients leaving the bank so the idea is : « Why would we need to compare the 3 countries at the same time ? ».

tableau chi square test

If we do an A/B test statistical test with Germany and France and we get a significant difference in the clients number leaving the bank between these 2 countries, then that would mean that in general, the country has a significant effect on the clients number who bank. Indeed, if we find by comparing Germany and France that the Germans are more likely to leave the bank than the French, we can consider that Spain will not change anything. Germans will always be more likely to leave the bank than the French. Maybe there will be a different relationship between Germany and Spain but there will always be a statistically significant difference between France and Germany with a larger number of clients leaving the bank in Germany than France.

Here is a way to confirm that this logic is true. There is a test and the participants of this test are German, Spanish and French. Imagine that this test was done without looking at what is happening in Spain. Now you get the result and you ask yourself the question : « Would the results changed if you added Spain ? ». The answer is « no » because there is no interdependence between Germany, Spain and France. That is, the decision to leave the bank in France and Germany doesn’t depend on Spain. And therefore, it’s quite correct to separate the categories by putting 1 aside to compare the 2 others. And as now we have 2 categories, we can do a Chi-square test with the online tool that we used in the previous article.

So let’s go back to our worksheet and put a country aside to compare only 2 countries. Select « Country » tab.

tableau chi square test

What we observe is that the difference between Spain and France is very small, so it wouldn’t be interesting to do a Chi-square test between Spain and France. It’s more interesting to do a Chi-square test between Germany and France and to prove that there is a statistically significant difference between these 2 countries. This will be enough to conclude that the country has a statistically significant impact on the clients number who leave the bank.

Selects « Country Actual » tab.

tableau chi square test

We will use the online tool of the previous article, click here  .

We will make a copy of « Country Actual » to have a bar chart with absolute values. Select « Country Actual », right-click and select « Duplicate ».

tableau chi square test

In « Show Me », select « horizontal bars ».

tableau chi square test

tableau chi square test

Removes « SUM (Number of Records )» from « Columns » and removes « Exited » and « Geography » from « Rows ».

tableau chi square test

tableau chi square test

In « Dimensions », move « Geography » in « Columns ».

tableau chi square test

tableau chi square test

In « Measures », move « Number of Records » to « Rows ».

tableau chi square test

tableau chi square test

In « Measures », move « SUM(Number of Records) » in « Label ».

tableau chi square test

tableau chi square test

In « Dimensions », move « Exited » in « Label ».

tableau chi square test

tableau chi square test

In « Dimensions », move « Exited » in « Colors ».

tableau chi square test

tableau chi square test

We also need total absolute values, which means the total number of men and women. There is a very fast way to get that. Right-click on the vertical axis and select « Add Reference Line ».

tableau chi square test

Then in « Value », click on the drop-down on the right and select « Sum » to have the total sum of the observations.

tableau chi square test

And in « Scope », you select « Per Cell » option to specify that you want the total sums for each category, male and female.

tableau chi square test

Now, we have the total sum at the top of the bars. We will modify labels to have the absolute values. In « Label », we will change « Computation » to « Value » and click on the « OK » button.

tableau chi square test

tableau chi square test

tableau chi square test

Here’s how to enter the data :

For « Sample1 » in #success, you enter 810 because there are 810 people who left the bank. For « Sample1 » in #trials, you enter 5014 because there are 5014 people in total.

For « Sample2 » in #success, you enter 814 because there are 814 people who left the bank. For « Sample2 » in #trials, you enter 2509 because there are 2509 people in total.

tableau chi square test

Here is the verdict : « Sample2 is more successful ». « Sample2 » corresponds to German’s clients and #success is :« yes, the client left the bank ». This verdict means that of all the clients from German are more likely to leave the bank than clients from France. And look, there is something important, it’s « p<0.001 ». This means that the « p » is strictly less than 0.001. As you can see, « p » value is very small, which concludes that the tests are statistically significant.

Ooh, there’s another thing I wanted to show you with the tab « age » with the 2 bar charts in parallel.

tableau chi square test

As you can see, there are many categories (more than 5) because each category corresponds to a 5-year ago group with clients of the bank aged from 15 to 90 years old. This is a lot of comparison but it would be a good exercise for you to find what are the 2 categories to compare that shows that there is a significant statistic difference.

I give you a hint, compare slices from 50 to 54 years old or from 35 to 39 years olds. In fact, you should compare all peer categories where you observe difference on this basic A/B test. Do a basic A/B test with absolutes values. Then do a Chi-square test to check if the difference is statistically significant, I mean, if the result is valid for the total number of bank’s clients.

This is a way to statistically validate the insights we see onTableau. You see, it’s not very difficult and it’s effective. Here is a way to find insights on Tableau and validate them.

Subscribe to my newsletter and share this article if you think it can help someone you know. Thank you.

-Steph

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Validate Data Mining In Tableau With A Chi-Square Test

validate validation

I have just enrolled in a Data Science course on Udemy  and I learned good stuff.

In this article we will start using statistics. Don’t worry we’ll do something simple, we’ll use the Chi-square test in a basic way. There is a special section to learn how to do statistics at an advanced level.

I’ll explain why we’re going to learn how to use the Chi-square test. The results we have with theses 2 bar charts are good. We see on theses 2 bar charts that age has a significant impact on the rate of client leaving the bank. We also see in which age groups the clients leaves the bank the most and which age groups the clients leave the bank the least. With that we have good insights.

In the A/B test « Gender », we can see that there is a correlation between the male and female sex and the choice to leave the bank. But as I said before, this A/B test is basic. The results of a basic A/B test visually shows us what is probably happenning in reality but we aren’t 100% sure of these results. To validate these results, we need do to use statistical tests like Chi-square test.

Doing a report based on basic A/B test is very risky and you can have completely false insights. I don’t advise you to do it (unless you want to leave your job). It’s for this reason that using Chi-square will help us to have strong insights.

Chi-square will allow us to know if our results are statistically significant. Our results are based on a sample of 10 000 clients and Chi-square test will tell us if these results are due to chance effects or if these results can represent all the client of the bank.

For example in our A/B test « Gender », we observed that in our sample of 10 000 clients, women are more likely to leave the bank compared to men.

tableau data mining science chi square test a/b test

Now, we aren’t sure if the results of this sample represent the behavior of all the bank’s clients.

To use basic Chi-square test, we use an online tool. Click here  .

tableau data mining science chi square test a/b test

On internet, there are plenty of websites to do a Chi-square test but we’ll use this one so that you can understand how it works. To do a Chi-square test, we need to use absolute values and in our A/B test we have percentage.

Let’s go back to Tableau. We’ll create a new tab with a version of A/B test with absolute values. In this way, we keep the A/B test with the percentages. Do a right-click on the « Gender » tab and select « Duplicate ».

tableau data mining science chi square test a/b test

Name the new tab « Gender Actual » to specify that it’s absolute values.

tableau data mining science chi square test a/b test

To have the absolute values, move « Number of Records » in « Measures » to the « Marks » area and put it over top of « SUM(Number of Records ».

tableau data mining science chi square test a/b test

tableau data mining science chi square test a/b test

Move « Number of Records » in « Measures » to « Rows » over « SUM(Number of Records ».

tableau data mining science chi square test a/b test

Cool, we have our absolute values.

tableau data mining science chi square test a/b test

We also need total absolute values, which means the total number of men and women. There is a very fast way to get that. Right-click on the vertical axis and select « Add Reference Line ».

tableau data mining science chi square test a/b test

Then in « Value », click on the drop-down on the right and select « Sum » to have the total sum of the observations.

tableau data mining science chi square test a/b test

And in « Scope », you select « Per Cell » option to specify that you want the total sums for each category, male and female.

tableau data mining science chi square test a/b test

Now, we have the total sum at the top of the bars. We will modify labels to have the absolute values. In « Label », we will change « Computation » to « Value » and click on the « OK » button.

tableau data mining science chi square test a/b test

tableau data mining science chi square test a/b test

Perfect, we have the total amount of observation at the top of each bar : 4543 women and 5457 men. We have what we need to use our online tool.

tableau data mining science chi square test a/b test

OK, I’ll explain how this tool works. « Sample1 » and « Sample2 » correspond to the independent variable « Gender ». You choose in which order you enter the data, « Sample1 » for men or the opposite. In our case, we use « Sample1 » for women and « Sample2 » for men.

« #success » corresponds to the result Y=1, which means in our case « yes, the client left the bank ».

« #trials » is the total number of observations, which means the total number of women in « Sample1 » and the total number of men « Sample2 ».

That’s how you enter the data :

  • For « Sample1 » in #success, you enter 1139 because there are 1139 women who left the bank. For « Sample1 » in #trials, you enter 4543 because there are 4543 women in total.

 

  • For « Sample2 » in #success, you enter 898 because there are 898 men who left the bank. For « Sample2 » in #trials, you enter 5457 because there are 5457 men in total.

tableau data mining science chi square test a/b test

Here is the verdict : « Sample1 is more successful ». « Sample1 » corresponds to women and #success is :« yes, the client left the bank ». This verdict means that of all the bank’s client, women are more likely to leave the bank than men. And look, there is something important, it’s « p<0.001 ». This means that the « p » is strictly less than 0.001.

tableau data mining science chi square test a/b test

« p » is the value that indicates whether an independent variable has a statistically significant effect on a dependent variable. In our case, the independent variable is « Gender » and the dependent variable is « Exited », which is : « yes, the client left the bank ». So « p » is strictly less than 0.001, which means that the independent variable « Gender » has a statistically significant effect on the dependent variable « Exited ». This shows us that out of the total number of bank’s clients, women are more likely to leave the bank than men.

This is how we use Chi-square test with this online tool. This is the same principle on all online tools that you can find on Google or DuckDuckGo . You can repeat these instructions that I gave you with other tools, you will get the same results.

It’s cool with the Chi-square we validated the A/B test and to specify that this A/B test is validated, we’ll color the tab in green.

Right-click on the tab, select « Color » and select « Green ».

tableau data mining science chi square test a/b test

tableau data mining science chi square test a/b test

Perfect, now we’ll validate another A/B test. Selects « HasCreditCard » tab.

tableau data mining science chi square test a/b test

We’re going to create an A/B test « HasCreditCard » only with absolute values. To save time, right-click on « Gender Actual » tab and select « Duplicate ».

tableau data mining science chi square test a/b test

We’ll remove the green color on the tab « Gender Actual (2) ». Right-click on the tab and select « Color » and « None ».

tableau data mining science chi square test a/b test

You rename the tab « HasCreditCard Actual ».

tableau data mining science chi square test a/b test

Move the variable « HasCrCard » over « Gender » in « Columns ».

tableau data mining science chi square test a/b test

tableau data mining science chi square test a/b test

Excellent, everything is ready to do a Chi-square test. We’ll remove « Exited » labels to better see the absolutes values. Make a click and drag out.

tableau data mining science chi square test a/b test

tableau data mining science chi square test a/b test

Perfect, let’s go back to our online tool. In this case, « Sample1 » is « no », which means client who don’t have credit card and « Sample2 » for « yes », which means clients who have a credit card.

That’s how you enter the data :

  • For « Sample1 » in #success, you enter 613 because there are 613 clients who left the bank. For « Sample1 » in #trials, you enter 2945 because there are 2945 clients who don’t have a credit card.
  • For « Sample2 » in #success, you enter 1424 because there are 1424 clients who left the bank. For « Sample2 » in #trials, you enter 7055 because there are 7055 clients who have a credit card.

tableau data mining science chi square test a/b test

Let’s look at the verdict, it’s « No significant difference ». « p » value is very high, it’s above 5%. This confirms that the independent variable « HasCrCard » has no statistically significant effect on the dependent variable « Exited ». That was the conclusion we had made when we had done the A/B test with percentages.

We had seen that there was 21% of « Exited » (clients who left the bank) in the category « no » and 20% in the category « yes ». With these results we concluded that most likely the variable « HasCrCard » had no impact on the rate of clients who left the bank. Chi-square test confirms our conclusion and we can put the tab « HasCrCard » in green to say that it’s OK.

Right-click on the tab « HasCreditCard » => « Color » => « Green ».

tableau data mining science chi square test a/b test

tableau data mining science chi square test a/b test

Excellent, now, you can do a statistical A/B test with 2 categories. Soon, we will do statistical A/B tests with more than 2 categories.

Share this article if you think it can help someone you know. Thank you.

-Steph

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Boost Your Marketing Based On Science (Part 1)

brain

I watched an Olivier Roland’s video and I learned good stuff.

Let’s see what neuroscience found on things that influence people to buy.

The book of Michel Badoc and Anne-Sophie Bayle-Touroulou « Le neuro-consommateur » (in french)  helps us better to understand this.

It’s a book that has been written for other researchers and academics. This is why this book is very interesting for entrepreneurs and consumers.

Here are the elements from this book to boost your marketing.

Until now, marketing and communication are based on the rational purchasing decisions and perceptions of advertising messages by the consumer. But neuroscience shows us that a huge part of our actions come from the subconscious part of our brain.

For A.K Pradeep  and Martin Lindstrom , only 15% of purchasing decision are rational. Current marketing studies limited in the accuracy of customer behavior. What customers say doesn’t always match what they do. Responses collected during a market study can be influenced by context, which disturbs responses. With neuroscience, we can directly communicate with the brain to try to improve marketing.

Here the elements found in neuroscience on the unconscious behavior of consumers.

  • Age et gender

  • Memory

  • Emotions and desire in the decision

  • 5 sens

  • Cognitive ergonomics, pricing, distribution and sales.

  • Subliminals relationships

  • Community and social networks.

Let’s go, we’ll see that in detail. We’ll start with age and gender because these 2 create behaviors and attitudes, sometimes, difficult to understand by a person who doesn’t belong to the same category.

Age

reptilian limbic neocortex brain

Reptilian brain

It’s the center of instincts and the satisfaction of primary needs. This mainly affects young children. They respect the leader who is the mother or the father but also the strongest person who can protect them in case of external danger.

Limbic brain

It’s the center of stress emotions, instinctive behavior and memory. This mainly influences teenagers. They are mainly attracted by new brands / products and original fashions that can distinguish or oppose them to adult fashions.

Teenagers are often interested in causes or subjects with a lot of emotions : social, humanitarian, ecological, fair trade, etc. They prefer emotional communication over rational information.

neocortex,

It’s the center of anticipation and decisions. This mainly affects adults.

With internet, we can see several big differences in the generational behavior of consumers. There are Digital Native and Digital Immigrants and these 2 categories require different approaches.

digital native immigrant

Digital Natives

These are the people who grew up with computers, smartphone and internet. They prefer to have jerky information without verb and without object complement. They can read in parallel information on several different media. They don’t need to structure their thoughts and they can have a random read mode. They feel emotions much more with colors and designs rather than structured text. They want things to go fast.

Digital Immigrants

They prefer a linear processing of information. They like the text’s logic. They wish to receive the information in a slow way with consistency in the structure. They want to keep their privacy and are wary of the information’s distribution on internet. They sometimes want to work alone.

Gender

gender male female

There is a distinct difference between the behavior of female and male consumers.

Female

The left hemisphere of the brain is more developed in women and they’re subject to the hormones influence. We can see more of this phenomenon when a woman becomes a mother. A woman like to communicate more that a man, she likes to talk and be listened to. She needs shares her ideas, feelings and emotions.

She’s very well oriented in time. A woman is less emotional than a ma but she is more sensitive because she has the sens of smell, hearing and touch more developed than a man.

Male

The right hemisphere of the brain is more developed in man and they’re subject to the influence of testosterone. A man is more emotional than a woman, but he expresses less his emotions. He likes action and competition. He’s very well oriented in space, which allows him to find shortcuts. The man’s view is very developed and is eroticized. This explains why the man is attracted by the nude, jewelry, makeup and clothes.

For these reasons, it’s easier to mee a man’s expectations compared to a woman’s expectations.

Differences

difference

Male

As you can see, man primarily uses his view to select a product or service that he can use to show his strength and seductive power. He likes offers that give short-term profits. He prefers simple and direct communication. He prefers images rather than text. Price is more important for the man than for the woman.

Female

A woman is more complex in her expectations. She processes information in a way that is both rational and emotional. A woman is not attracted by nudity. She is attracted by a neat person with harmonious clothes and neat hands. In the case of a salesman, a woman has no preference for a man of a woman. This is influenced by several elements : voice, smell, facial expression, capacity to listen and quality of answers of the salesman.

A women prefers written and documented communication. She likes social media because she can express her ideas and meet people who share her points of view. She filters rational messages through her emotions. She likes positive communications. Before selecting a product/service, she will compare it with competitors and get information with her friends, co-workers and other people with experience.

A woman is less impulsive than a man even if a purchase can serve as an antistress. For a woman, the touch’s quality and the smell can influence a purchase like clothes.

This is the end of the 1st part.

Share this article if you think it can help someone you know. Thank you.

-Steph

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Masturbation And Sport

hand draw

I watched a Jamcore DZ’s video  and I learned good stuff.

My intention is to explain masturbation’s effect on a sport activity without being vulgar. Masturbation is a normal activity for some people and abnormal for others. In some religions, it’s a forbidden or ignoble activity but it’s an activity that most people do.

Type of person

type person

The open minded person

For this person, masturbation is a normal activity because it’s natural and give a good mood. It’s not something bad.

The guilty person

For this person, masturbation is an abnormal activity, ignoble but despite that, this person does it and still feels guilty after masturbation.

The obsessed person

For this person, masturbation is an obsessive activity. This person could masturbate every hour, every day.

The bored person

For this person, masturbation is an activity to kill boredom. He’s a person who has nothing to do in life or in the day and doesn’t know what to do, masturbation.

How the body reacts

body reaction

chart masturbation dopamine orgasm prolactin testosterone

  1. The intensity of masturbation increases (black line)

  2. There is a release of hormones, it’s dopamine. Before masturbation, there is a first release of dopamine that cause sexual arousal and there are other dopamine release during masturbation (blue line)

  3. Sexual arousal during masturbation will start the process to have the explosion, this explosion is orgasm (red line).

  4. Once the orgasm has happened, there is a release of hormones, it’s prolactin. Prolactin causes the loss of interest to continue masturbation. You satisfied and you don’t want to continue to masturbate. In some situation, prolactin can make you feel guilty (green line).

Stop masturbation for 1-3 weeks

stop

chart masturbation dopamine orgasm prolactin testosterone

There is a black line in the middle of the chart. This is the line of testosterone. When you stop masturbation for 1-3 weeks, there is an increase in testosterone rate. But after 3 weeks, the testosterone rate returns to normal. You have to base on your normal testosterone rate to see if your testosterone is affected by anything.

It’s possible that during masturbation, the testosterone rate is below your normal testosterone rate. In this case, it’s another problem and it’s necessary to see your doctor for more details.

Most people think that masturbation makes you lose testosterone. So if masturbation makes you lose testosterone, it means that masturbation also make you lose muscles. The truth is that this myth is wrong.

Masturbation and gain muscle

anatomy muscle

The answer is « No » because the elements that influence muscle gain are training program, nutrition and rest/sleep. The only thing that masturbation does before or after a training session is the increase in heart rate.

Warning

Now that you have this information, it doesn’t mean that I encourage you to masturbation several times a day, every day. You do this when you want according to your desires but in moderation.

Here are several scientific studies on masturbation and testosterone :

  • Endocrine response to masturbation-induced orgasm in healthy men following a 3-week sexual abstinence. Click here . 
  • 3 Weird but Surprisingly Effective Tricks & Tips to Raise Natural Testosterone Levels. Click here
  • Lack of sexual activity from erectile dysfunction is associated with a reversible reduction in serum testosterone. Click here.
  • Studies on the relationship between plasma testosterone levels and human sexual activity. Click here
  • Acute changes in plasma testosterone levels and their relation to measures of sexual behavior in the male house mouse (Mus musculus). Click here
  • Effects of ejaculation on levels of testosterone, cortisol, and luteinizing hormone in peripheral plasma of rhesus monkeys. Click here
  • Relationship between sexual satiety and brain androgen receptors. Click here .
  • Increased estrogen receptor alpha immunoreactivity in the forebrain of sexually satiated rats. Click here
  • A study of the prostate, androgens and sexual activity of male rats. Click here
  • Androgen Receptors: 5 Ways to Increase the Density and Sensitivity of the AR. Click here
  • Scientists visit sex club for research into testosterone levels. Click here
  • Male and female salivary testosterone concentrations before and after sexual activity. Click here
  • Sex and Testosterone: Most Enjoyable Way to Boost Male T-Levels Naturally. Click here

Share this article if you think it can help someone you know. Thank you.

-Steph

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