Body mass index, sexual difficulties and sexual satisfaction among people in regular heterosexual relationships : a population-based study

Background/Aims:  The aims of this study were to clarify the relationship between body mass index (BMI) and sexual difficulties and to investigate if BMI influenced sexual satisfaction, over and above the effects of sexual difficulties.

Methods:  Cross-sectional analyses of a nationally representative computer-assisted telephone interview. Eight thousand, six hundred and fifty-six respondents were recruited by random digit dialling in 2004–2005. Only those in a sexually active, heterosexual relationship were included in the current analyses.

Results:  After adjustments for demographic factors, both overweight and obese male and female participants were more likely to report worrying during sex about whether their body was unattractive. Among women, associations were also found between higher BMI and lack of interest in sex. No other significant associations between BMI and sexual difficulties were evident. There was an association between BMI and extreme physical pleasure for women but not men over and above the effects of sexual difficulties, with obese women being more likely than normal weight women to report extreme physical pleasure. No associations were found for either men or women between BMI and whether or not they reported extreme emotional or sexual satisfaction with their relationship.

Conclusions:  With the exception of body image difficulties, there is little association between BMI and self-reported sexual difficulties. Furthermore, extreme sexual and emotional satisfaction appeared to be associated with the presence or absence of sexual difficulties and not overly influenced by BMI. Overall, clinicians and patients should be aware that being overweight is not necessarily detrimental to sexual functioning.

Object oriented regular expressions

Regular expressions are used to parse textual data to match patterns and extract variables. They have been implemented in a vast number of programming languages with a significant quantity of research devoted to improving their operational efficiency. However, regular expressions are limited to finding linear matches. Little research has been done in the field of object-oriented results which would allow textual or binary data to be converted to multi-layered objects. This is significantly relevant as many of todaypsilas data formats are object-based. This paper extends our previous work by detailing an algorithmic approach to perform object-oriented parsing, and provides an initial study of benchmarks of the algorithms of our contribution