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A walk in the Park

This blog is dedicated to everyone who has struggled with Community Medicine. Through my posts I hope to simplify and demystify community medicine. The emphasis will be on clarifying concepts rather than providing ready-made answers to exam questions.

Feedback is crucial for the success of this endeavour, so you are encouraged to comment and criticize if you cannot understand something.

If you want a topic to be discussed sooner rather than later, please let me know via

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Twitter: @DocRoopesh

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A single example may not be able to explain 100% of a given topic, so multiple examples may be provided to explain different parts of a single concept.

If something doesn’t seem right:

a. Write to me about it (at communitymedicine4asses@yahoo.com), and

b. Cross check with another source (textbook, expert, etc.)

I hope that my exertions will make your experience with community medicine seem like a “Walk in the Park”

Note 1. Those who wish to contact me on facebook are requested to kindly send a personal message introducing themselves along with the request. This will help save time and effort of all concerned. Please do not expect me to visit your page to try and identify you/ your areas of work/ interest, etc. It is common courtesy to introduce oneself to another when interacting for the first time. I am merely requesting that the same civil courtesy be extended here, too. Henceforth, I may not accept any friend requests/ requests to join the group on facebook unless accompanied by a note of introduction (except when I already know the sender).  

Note 2. Please understand that this blog (and the corresponding facebook page/ group) is maintained in my spare time. I have a full time job, and am available to pursue these activities only after regular working hours (after 5 pm Indian Standard Time). However urgently you may wish to receive a response from me, I will be able to respond only upon returning home from work (I am offline the rest of the time).

Note 3. Please mind your language when interacting with me/ in the group linked to this blog. Rude/ offensive language will result in expulsion from both my friends list and the said group.

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Types of variables Part 2: Explanatory and Response variables

Disclaimer: This article is primarily intended for an online group of post graduate students in Community Medicine that I am involved with. The group was created to provide supplemental instruction to members on topics of common interest. Instruction is in bite-sized portions, since all members are busy PG students. Conceptual understanding is emphasized. Membership to that (Whatsapp) group is through invitation only. However, others interested in participating in the discussions and related activities in Google classroom may indicate the same by sending me a message on Facebook.

In the previous article, variables were classified based on their underlying scale of measurement. However, variables are also classified based on their relationship with the outcome of interest.

When a variable is suspected to influence the outcome, it is termed the explanatory/ independent variable.

When a variable is suspected to be influenced, it is termed the response/ outcome/ dependent variable.

Example: One wishes to determine the relationship between gestational age and fetal weight. Here, gestational age influences/ explains fetal weight; fetal weight is dependent upon gestational age. Therefore, the explanatory variable is gestational age, while the response variable is fetal weight.

In other words, the variable that is influencing is the explanatory/ independent variable, while the variable that is being influenced is the response/ outcome/ dependent variable.

Note: The terms independent variable and dependent variable are also used to describe relationships between variables. If the values of one variable are not influenced by another variable, it is independent of the other variable. However, if the values of one variable are influenced by another variable, the latter is said to be dependent on the former. The dependency is also described using the terms paired and unpaired variables: where dependency exists between values of variables, the variables are said to be paired, else they are unpaired.

Example: The scores obtained by boys and girls in a test are independent of each other (boys’ scores are not influenced by girls’ scores). However, scores obtained after a revision class are dependent on (influenced by) the scores obtained before the revision class (pre-post scenario).

Links to relevant previous articles:

Link to article on types of variables part 1:


Link to article on scales of measurement: