9. Money for upkeep on campus: 1 for “Not enough”, 2 for “Just enough”, 3 for
5.16 Factors that drive sexual activities in the two universities Research question 1.7.5
Table 5.23 c: Cross tabulation of sexual activities (Section B) against risk assessment of students (Section F) ALL
Variable Risk assessment of students
Count 2 df Asymp. Sig
(2-sided)
Low Medium High
When did you have sex for the first time? 43.420 10 .000
No response Elementary school High School
First year in University After year in University Never had sex
1 2 7 4 1 4
5 83 216 74 39 77
12 67 403 137 106 208
How many sexual partners since first experience 42.448 10 .000
No response None 1.00 2.00 3.00 More than 3
1 4 8 2 2 3
6 73 141 83 51 142
7 222 320 142 81 162
How often did you use condom in the last three months? 27.065 6 .000 No response
Always Sometimes Not at all
1 7 3 7
21 174 175 94
46 376 222 241
When do you best enjoy having sex with your partner(s)? 62.641 8 .000 No response
When I am relaxed After an all-night party After a good alcoholic After a shot of drug
1 12 2 1 1
33 319 42 61 14
71 708 35 36 9
Who of the following would you have sex with for money or a favour? 95.766 14 .000 No response
A business man A lecturer
A senator/Minister/Commissioner A banker
A brilliant course mate All of the above None of the above
2 2 0 1 0 0 1 10
3 17 23 27 13 41 55 309
11 29 17 26 14 52 30 750
5.16 Factors that drive sexual activities in the two universities
5.16.1 Factors that drive sexual lifestyles
Some of the factors has been were covered under Aim 1.8.5. To identify the factors that drive sexual activities on the respective campuses the socio-demographic variables were cross tabulated against the sexual activities variables and layered with the University variable. Those variables that have significant relationship (P<0.05) are taken as factors that have effect on the corresponding risky sexual behaviour in the sexual activities. The data is presented in Table 5.24 a-b.
For UNAD gender is a major factor for all risky behaviours except in ‘Do you know the HIV status of your partners?, ‘Did you use condom in the last three months?’ and ‘Did you use condom during your last sexual intercourse?’. Other variables identified for UNAD are ‘How old are you now?’ (for sex debut), level of study (for sex debut and sex for money/favour), marital status (for condom use in the past three months, when do you best enjoy sex? and sex for money or favour), where grown up (for sexual debut, ‘Do you know the HIV status of your partners?, and ‘Do you know your own HIV status?), number of children (‘How many sexual partners since sexual debut?, condom use in the past three months, and when do you best enjoy sex?), family resources (for do you know the HIV status of your partners? and do you know your own HIV status?), how old were you in your first year (condom use in the past three years) and religion (sex for money/favour) and stipend (how many sexual partners and do you know your own HIV status?)
Table 5.24 a: 2 2-tailed significances from cross tabulation of Section A against Section B for UNAD*
VARIABLES B1 B2 B3 B4 B5 B6 B7 B8 B9 B10
A0 .000 .000 .643 .046 .001 .408 .381 .133 .009 .038
A1 .185 .790 .000 .066 .511 .644 .003 .121 .692 .464
A2 .020 .161 .000 .585 .182 .421 .301 .946 .233 .854
A3 .001 .509 .095 .574 .431 .410 .515 .422 .193 .042
A4 .379 .630 .902 .100 .640 .393 .001 .202 .009 .013
A5 .138 .005 .296 .367 .819 .340 .001 .640 .026 .239
A6 .489 .760 .000 .093 .602 .883 .515 .230 .120 .000
A7 .023 .146 .866 .230 .027 .005 .300 .714 .816 .790
A8 .886 .142 .028 .742 .033 .000 .528 .945 .954 .240
A9 .389 .005 .094 .359 .341 .000 .535 .332 .717 .083
Table 5.24 b: 2 2-tailed significances from cross tabulation of Section A against Section B for UNIZULU
VARIABLES B1 B2 B3 B4 B5 B6 B7 B8 B9 B10
A0 .000 .000 .284 .039 .000 .000 .001 .004 .000 .000
A1 .000 .000 .137 .000 .227 .031 .001 .000 .000 .172
A2 .000 .000 .040 .000 .000 .000 .000 .000 .000 .023
A3 .000 .418 .095 .000 .023 .001 .001 .000 .004 .072
A4 .003 .001 .000 .651 .042 .077 .000 .003 .022 .374
A5 .000 .000 .000 .000 .000 .018 .000 .000 .000 .419
A6 .080 .191 .013 .779 .025 .841 .622 .909 .861 .810
A7 .104 .405 .001 .391 .009 .908 .075 .167 .024 .076
A8 .270 .095 .406 .832 .000 .119 .324 .872 .834 .088
A9 .016 .411 .004 .483 .363 .967 .743 .619 .089 .818
*See questionnaire (Appendix A) for keys to variable labels.
For UNIZULU the factors are more complex in the sense that gender, age at first year, age now, are factors for all the risk factors except ‘Do you know the HIV status of your partners and sex for money where age now is not a factor. Level of study is a factor for all risks except number of sexual partners and sex for money/favour. Marital status is a factor for sex debut, number of sexual partners, knowledge of HIV status of partners, condom use in the past three months, condom use in the last sex, and when sex is best enjoyed. Number of children is a factor for all variables of risk except sex for money/favour. Where grown up is a factor for knowledge of HIV status of partners and when sex is best enjoyed? Family
resources and stipend are factors for knowledge of HIV status of partners and sex debut respectively.
The risk factors of UNAD appear to be driven by one predominant factor, gender, which is a factor in six risky activities. Marital status, number of children and where grown up contribute to three factors each while level of study, family resources and stipend contribute to two each. The impact of religion and age appear minima at one factor each.
UNIZULU’s risky sexual activities appear to be driven by a more complex web of factors and at greater impact than UNAD. Gender and age now drive nine factors each, number of children has effect on eight, age at first year and level of study drive six, where grown up drives two and religion, family resources and stipend only have effects on one factor each.
The UNIZULU scenario reveals interplay between pre-entry and post-entry factors routed in active sexual activities prior to entering university (manifested in adolescent sexuality and high single parenthood) and an environment far removed from centres of relaxation on campus, which leaves sex as the most practical alternative. For UNAD the undercover prostitution that has been widely reported among Nigerian undergraduates are driven by gender, either as women that offer their bodies for money/favour or by male pimps that recruit them for the trade.
Summary
This Chapter focused on presentation of results and the analyses of data extracted from both descriptive and inferential statistical analyses. Evidence was provided for good internal reliability of instrument using pre-test/post-test analysis as well as on the entire
study population. The results obtained from the analyses are fully discussed and the results of hypothesis testing presented.
Chapter 6 will cover the main findings of the study and suggestions for using the findings to formulate prevention strategies to suit the university system, conclusion and suggestions for further studies.