I literally read a study two days ago that said the opposite. Married with children were happiest, followed by married without children, followed by unmarried without children, with unmarried with children being last. The study was conducted by GSS (General Social Survey), so it's pretty reliable. It was conducted a couple years ago, and is based on women's responses in the 18-55 age bracket. Findings for men were the same ranking, though married without children and unmarried without children were almost on par, whereas it was an 8% gap for women.
Social media and mainstream media are replete with stories suggesting marriage and parenthood are not fulfilling, especially for women. Not surprisingly, many Americans now believe the key to being happy is a good education, work, and freedom from the encumbrances of family life—not getting...
www.aei.org
Although GSS is a reputable survey group, the problem with modern surveys is that there can often be a lack of integrity or competence in conducting them. The language is often loaded, the questions can be a bit misleading, and the available responses to choose from may not encompass the full range that would be applicable. All these can skew the results a certain way...and usually in a way that more supports the ideology of those conducting or paying for the survey. And even once data is collected, the interpretation of said data is also prone to further skew, and then add on top of that how the data is presented.
Just as a for instance, the above link reported the data of only those who said they were "very happy". Whereas the data collected by the survey has things broken down by "very happy", "happy" and "not happy". By presenting only one data point, the article could skew you into believing a majority are unhappy in each instance. So how the data is reported can definitely play a role.
The reason I bring this up is because social media is full of claims that childless, unmarried women are super happy. Occasionally the people saying such will reference a survey or research, but as soon as you dig below the surface you realize something is askew with the data they're basing their opinion on. I can't tell you the number of times I've found this because sometimes the claims are so outlandish that I just have to dig deeper, only to find the claims are wrong.