Introduction

Street sex workers (SSWs) are the most vulnerable groups for STDs. Unsafe sex and careless lifestyle become a part of their life. Commercial sex plays a critical role in the heterosexual transmission of HIV. Hong and Li (2008) conducted behavioral studies on commercial sex workers in China. According to Hong and Li (2008), sex workers in China are young, mobile, most of them have both commercial and non-commercial sex partners with low rates of consistent condom use and high rates of STD infection. Risks associated with the brothel-based sex and knowledge in sexual health of sex workers were also emphasized in many literatures. In most cases, sex workers were found with a very little knowledge about safe sex (Huang et al, 2004). A study on Chinese entertainment workers conducted by Yang and Xia, (2006) explored the risky sexual behavior and lack of knowledge on healthy sexual partnership. In fact, most of the research was carried on brothel or hotel based sex workers. Apart from this, Wong et al (2006) studied the health complications and unhealthy sex trade of street sex workers in Hong Kong. Inspired by the work of Wong et al (2006) we would like to focus on the study on some pain related health problems of street sex workers in Rajshahi city of Bangladesh.

Street sex workers suffer from various health complications. Moreover, they are highly vulnerable to STDs and HIV (Wong and Wang, 2003). Usually sex trade is not legal in Bangladesh except in 15 brothels. A study on commercial sex workers postulated the scenario of socio-economic consequences that bounds the sex worker to involve into it (Nessa et al, 2005). They are not conscious about their health problems. Moreover, they do not get proper health care and nutrition facilities. As a result, they suffer from a number of sexual health complications like chest pain, joint pain, back pain, waist pain, vaginal pain, high and low blood pressure, hypertension etc. Eventually, all these complications may be resulted from careless over sex and imbalanced physical growth with nonstandard blood and pulse pressure. Our aim in this study is to explain the stark reality behind the plight of some pain related problems of sex workers.

Data and Methods

Data Collection

Methodology

Statistical Models

Multivariate logistic regression model is used to study the effect and interaction of categorized variables (Hosmer and Lemeshow, 2000). Another multivariate model that is a sibling of logistic regression is linear probability model (LPM) where estimation technique is quite different than the logistic transformation. The general expression of the linear probability model (LPM) is of the form (Gujarati, 1995) given below

Figure 1

Here,X_k ’s are independent variables and β_k is the coefficient of X_k , β₀ is constants and ε_i is the error term. The dependent variable explaining the chest pains can be expressed as

Figure 2

Dichotomous variables considered here are condom use (CU), length of service (PY) and average number of clients per night (NCPN) which are expressed as

Figure 3

Figure 4

Figure 5

Explanatory variables from different categories of body fat, pulse pressure and blood pressure. To perform certain analysis like logistic regression and linear probability model (LPM) we have used forward selection procedure in which the most significant variable (categorical variable for body fat, blood or pulse pressure) is included at the first stage and then include another variable that seems to be the most significant among the remaining variables. Finally, a set of significant variables are gathered. Variables found to be common in both fitted models (logistic and LPM) with same sign of coefficients are hypothesized to be most influential.

Many variables may cause health complications, however, the strength of causing health complications by all variables are not same. Even the direction or influence of those variables may be different based on the type of the fitted model, that is, a variable may be found significant while fitting a logistic regression but may be insignificant whilst fitting a linear probability model. But if the variable bears a strong influence on the dependent variable it is most likely to be significant in both models (LR or LPM) with the same sign of coefficient, that is, the variable is model invariant. Obviously, model invariant variables are stronger compared to other variables. Thus, we are interested in some model invariant variables which are assumed to have strong influence on dependent variable.

Results and Discussion

The population under study is very peculiar with clandestine nature as sex trade out side fifteen brothels are deemed illegal as per the constitution of Bangladesh. The social characteristics (Table I) of sex workers are very perilous with more than 10% of them are adolescents (aged 15-19) and more than one-fifth of them are young adult (aged 20-24). Consequently, more than two-fifth of the SSWs commence in sex trade within their young adulthood. The stark reality is that more than 90% of them start this profession due to financial hardship. Nearly three-fourth of the SSWs are married and illiterate. Astonishingly, in an average a SSW serve for 3 clients per night and 4 nights per week, that is, average number of clients per week is 12. Consequently, their average monthly income is nearly 2850 taka (nearly 40 US dollars), which is really a hand to mouth economy. Although SSWs are vulnerable to STDs, astonishingly, more than half of them (54.5%) do not consult the physician on regular basis and more than one-third of them do not use condom (Table I).

Figure 6

Table I: Distribution of respondents by socio-economic characteristics

Some health characteristics are studied and some health related indicators are also computed to depict the health status and physical growth of SSWs (Table II). Although three-fourth of the SSWs have normal blood pressure, some of them have hypotension (low blood pressure) and hypertension (high blood pressure). Roughly, more than one-fifth of the SSWs are suffering from either hypotension or hypertension problem. Though majority of them have normal blood pressure, more than half of them have high pulse rate.

Body fat level is an important indicator to know the body fitness of a person. It is depicted that around half of the SSWs have normal body fat, that is, they are physically fit. However, nearly one-third of them have already got over body fat in their body (Table II). Consequently, more than half of the SSWs are suffering from the different kinds of physical pains in vagina (64.8%), chest (49.4%), joint (56.8%), back (60.2%) and waist (61.4%).

Figure 7

Table II: Distribution of respondent by some selected health characteristics

To detect individual factor of different types of pains like chest pain, joint pain, back pain, waist pain and vaginal pain Multiple Logistic Regression (MLR) and Linear Probability Model (LPM) were used to identify the consistent factors that are explained to stronger the risk of such health problems. Several factors may be associated with the risk of these problems. The following Table III and Table IV show the estimated parameters assuming logistic and linear probability model.

Figure 8

Table III: Estimate of parameters assuming logistic approach

Figure 9

Table IV: Estimate of parameters in LPM

From Table V, we found number of clients per night (NCPN) as common factor for explaining the risk of chest pain from both the fitted models. Thus, we may envisage that the service to the more clients that leads to an over sex (3 or more clients per night) significantly increase the risk of chest pain. Two common factors length of service (PY) and normal body fat (BFN) positively affect the back pain, that is, long service in this profession and increased body fat deviating from the normal level increase the risk of back pain. For joint pain, we get two common factors over body fat (BFOV) and low blood pressure (BPLOW). As much as the over body fat gains so much the risk of joint pain depicts but as much as the low blood pressure increases to normal level so much the risk of joint pain reduces. Consequently, increased length of service and over body fat increases the risk of feeling waist pain. As the body fat increases from its normal level and the over sex (serving with more clients) is depicted, the vaginal pain is found to be increased, however, this risk expected to be reduced with the increase in the service length. The results and explanations are solely from the view of statistical findings and may not be analogous to the biological reasoning. Due to our limitations in human physiology and medical science, we keep the sophisticated biological explanations for some curious biologist. But, these common factors may be very interesting in the sense of keeping less physical pain among SSWs apart from the biological mechanism behind these pains.

Figure 10

Table V: Common factors for pain problems

Conclusion

Street sex workers are deprived from most of the urban facilities though they are living in metropolis. Most of the curses in humans like illiteracy, ignorance about own physical fitness, nutritional status and unconsciousness of sexually transmitted diseases (even no use of condom) make them very vulnerable for the society. Thus, priority should be given to raise the consciousness of condom use among SSWs to protect the outbreak of STDs. Consequently, proper nutrition of SSWs is necessary to keep the body fit for this job. Since most of the physical pains are found as the indirect cause of physical fitness, so to make sure of good health, good remuneration is necessary as proper nutrition is not possible with the subsistence economy. Therefore, both government and non-government initiatives providing different supports would save the life of SSWs as well as would safe from the outbreak of STDs.