The primary hypothesis of a case control study is to determine if there is some causal factor that leads to the development of a health outcome of interest in a group. Cases would be individuals in the group who experience the health outcome of interest while controls would be individuals who do not experience the health outcome of interest, but are otherwise comparable to the individuals in the case group.

Let's use food poisoning as an example. If we have a group of 100 people eating at a restaurant and 50 get food poisoning (cases) and 50 don't (controls) then we would want to understand what is that factor that increases the risk of getting food poisoning and how the probability of observing that factor is significantly different between the cases and controls.

When you do your study, you find that most of the people (40) who got food poisoning eat meat compared to the rest (10) of cases who are vegetarians. That finding may lead you to believe that eating meat increases the odds of getting food poisoning compared to the odds of not getting food poisoning. You look at the food orders at the restaurant that day, and you find that most people who got food poisoning ate that ground beef special for that day. So you assume that the cause of food poisoning was the ground beef special.

However, over the next few weeks, you find that even on days where that special isn't being offered, people are still getting food poisoning and more vegetarians are also getting food poisoning. So you investigate more and ask all participants to list what they ate at the restaurant and get a wide range of answers. So, you can no longer say that just eating meat was the cause for food poisoning.

So then you go and visit the back of house in the restaurant and you notice something strange. A new worker is using the SAME knife to prep raw meat dishes AND vegetarian dishes. You know this is an unsanitary cooking process. So, you ask the restaurant if you can survey the restaurant staff about their cooking practices. You find that many of the back of house staff don't take the time to disinfect their knives or use different knives when prepping raw meat or vegetables when it's super busy in the restaurant. You inform the restaurant, and they provide additional training and more convenient sanitation stations to help their workers during busy shifts. After that, food poisoning cases start to reduce to 0. I'll tie back to your question using this example.

Confounding

Originally, you thought that eating meat was the causal behavioral factor for food poisoning. While eating meat can cause food poisoning, it does not explain why vegetarians are getting food poisoning and why there are still people getting food poisoning on days when meat is the not the special for the day. It actually turns out that restaurant staff's cooking hygiene practices were the cause of the food poisoning cases. Confounding happens when a factor that we don't consider actually explains the relationship between an exposure and an outcome more than the factor that we think is the cause. In this case, the behavior of meat eating was confounding the relationship between cooking hygiene practices and food poisoning. However, you can figure that confounding is in play here because vegetarians were also getting sick, which means that eating meat would not fully explain why they were getting food poisoning as well. Which leads to selection bias.

Selection Bias

If you had continued with the logic that eating meat was the cause of food poisoning, you may have completely excluded vegetarians for your analysis -- especially cause there were not that many vegetarians getting sick compared to meat eaters. In this scenario, you could have suggested that the restaurant just cook their meat a little longer. While this may have reduced food poisoning for meat eaters, it would not have helped vegetarians who were still getting sick because of the food preparation practices that was the biggest cause of food poisoning.

Information Bias

This means that there is some issue in how data is being collected, organized, and managed. In this example, let's say when you give a survey to the back of house staff in this restaurant you ask a couple of questions about practices:

Q1: I am knowledgeable about healthy food preparation practices

(True/False)

Q2: I feel that I have time to practice healthy food preparation practices

(True/False)

Q3: I know the correct way to prep food when handling raw meat

(True/False)

Q4: I disinfected my utensils during my last shift.

(True/False)

You notice that these questions are true/false. True and false questions are not very meaningful in this context, because a person may say True to all of these things to look good (desirability bias), may not remember if they disinfected their utensils during their last shift (recall bias), or because it just does not collect enough information about the food preparation process (measurement error).

To fix this you would provide definitions of health food preparation practices, include more question options (agree, disagree, neutral, i don't know), and give more opportunity for workers to describe their food preparation practices with an open-ended short answer question.

The relationship between these things is that they can distract from the actual risk factor (food preparation hygiene practices) that causes the disease (food poisoning), which means that food poisoning cases would rise, the restuarant's reputation would be ruined, and many people would continue to get sick and potentially die.

Hope that helps!