Background characteristics
The descriptive analysis of the study population by the background characteristics were presented in Table 1 below. In the three countries surveyed, the proportion of respondents for both the male and females aged 15 to 19 years ranges from 65.7% (Ghana) to 64% (Rwanda). Only South Africa had less than 60% of those between age 15 and 19 years for both males and females. Rwanda had 39.3% of the male adolescent, 38% male adolescents were from Ghana. South Africa recorded the highest proportion of the males and females without any employment at the time of the survey at 91.4% and 83.7% respectively, while the least is Rwanda at 43% females and 34.6% for the males. With regards to education attainments, respondents who had secondary education attainment were the majority, 87.9% for females and 82.4% males (South Africa), 73.5% females and 72.4% males (Ghana) and 44.4% females and 38.6% males (Rwanda). In terms of household size, South Africa recorded the highest proportion of those from a household made up of 1 to 4 members among the males at 45.7%, 37.5% (Ghana) and 34.7% (Rwanda).
Additionally, Rwanda recorded the highest proportion of male and female respondents who are living in a neighbourhood with a low poverty level at 73.8% males and 69.6% females. Ghana and South Africa had more than 40% of their male and female youth living in a neighbourhood with high poverty levels. In terms of community media accessibility, those with no access ranges from 34.6% females (South Africa), and 18.7% females (Ghana) to 10.5% females (Rwanda). With regards to the community occupation, more than 50% of males and females did not have any job from all the countries surveyed. Apart from South Africa which recorded the highest proportion of those living in a community with low education for the males and females at more than 70%, the rest of the countries had a little above 50% of those living in a community with low education. More so, apart from South Africa which recorded the highest proportion of young people who resided in the urban areas, the rest of the surveyed countries had the highest proportion residing in the rural areas, ranging from 73.5% males and 71.2% females (Rwanda), and 54.3% males and 49.3% females (Ghana) to 53.1% males (South Africa). In all, there was substantial representation across gender in all the countries surveyed.
Table 1
Background characteristics
|
|
Ghana
|
|
|
|
Rwanda
|
|
|
|
South Africa
|
|
|
Female
|
|
Male
|
|
Female
|
|
Male
|
|
Female
|
|
Male
|
|
Characteristic
|
Freq.
|
%
|
Freq.
|
%
|
Freq.
|
%
|
Freq.
|
%
|
Freq.
|
%
|
Freq.
|
%
|
Respondent age
|
|
|
|
|
|
|
|
|
|
|
|
15-19
|
1,623
|
65.7
|
886
|
62
|
2,676
|
64.0
|
1,278
|
60.7
|
1,461
|
55.7
|
704
|
55.5
|
20-24
|
849
|
34.3
|
542
|
38
|
1,502
|
35.9
|
827
|
39.3
|
1,160
|
44.3
|
564
|
44.5
|
Employment status
|
|
|
|
|
|
|
|
|
|
|
|
No
|
1,544
|
62.6
|
642
|
45
|
1,791
|
43.0
|
726
|
34.6
|
2,396
|
91.4
|
1,061
|
83.7
|
Yes
|
924
|
37.4
|
785
|
55
|
2,371
|
56.9
|
1,370
|
65.4
|
225
|
8.6
|
207
|
16.3
|
Respondent education attainment
|
|
|
|
|
|
|
|
|
|
|
Primary and less education
|
555
|
22.4
|
337
|
23.6
|
2,249
|
53.8
|
1,238
|
58.8
|
157
|
5.9
|
172
|
13.6
|
Secondary
|
1,817
|
73.5
|
1034
|
72.4
|
1,855
|
44.4
|
813
|
38.6
|
2,306
|
87.9
|
1,045
|
82.4
|
Higher
|
100
|
4.0
|
57
|
4
|
74
|
1.8
|
54
|
2.6
|
158
|
6.0
|
51
|
4.0
|
Household size
|
|
|
|
|
|
|
|
|
|
|
|
1 - 4
|
906
|
36.6
|
536
|
37.5
|
1,189
|
28.5
|
730
|
34.7
|
977
|
37.3
|
579
|
45.7
|
5 - 6
|
775
|
31.3
|
416
|
29.1
|
1,388
|
33.2
|
662
|
31.4
|
750
|
28.6
|
310
|
24.4
|
7 +
|
791
|
32
|
476
|
33.3
|
1,601
|
38.3
|
713
|
33.9
|
894
|
34.1
|
379
|
29.9
|
Neighbourhood poverty
|
|
|
|
|
|
|
|
|
|
|
|
Low (wealth low)
|
1,400
|
56.6
|
715
|
51
|
2,910
|
69.6
|
1,554
|
73.8
|
1,441
|
54.9
|
665
|
52.4
|
High (wealth high)
|
1072
|
43.4
|
713
|
49.9
|
1,268
|
30.3
|
551
|
26.2
|
1,180
|
45.0
|
603
|
47.6
|
Community media access
|
|
|
|
|
|
|
|
|
|
|
No access
|
462
|
18.7
|
125
|
8.7
|
437
|
10.5
|
200
|
9.51
|
908
|
34.6
|
293
|
23.1
|
Not regular
|
812
|
33
|
318
|
22.3
|
836
|
20.0
|
229
|
10.9
|
482
|
18.4
|
337
|
26.6
|
Regularly
|
1198
|
48.5
|
985
|
69
|
2,900
|
69.5
|
1,674
|
79.6
|
1,231
|
46.9
|
638
|
50.3
|
Community occupation
|
|
|
|
|
|
|
|
|
|
|
|
Not working
|
1469
|
59.4
|
561
|
39.3
|
1,436
|
34.4
|
693
|
33
|
2,336
|
89.1
|
988
|
77.9
|
Professionals
|
115
|
4.6
|
71
|
4.9
|
59
|
1.4
|
35
|
1.7
|
113
|
4.3
|
30
|
2.4
|
Sales/unspecified
|
434
|
17.6
|
97
|
6.8
|
252
|
6.0
|
120
|
5.7
|
15
|
0.6
|
13
|
1.0
|
Agriculture
|
270
|
10.9
|
461
|
32.3
|
2,267
|
54.4
|
922
|
43.9
|
33
|
1.3
|
53
|
4.2
|
Manual
|
183
|
7.4
|
236
|
16.5
|
155
|
3.7
|
330
|
15.7
|
124
|
4.7
|
184
|
14.5
|
Community education
|
|
|
|
|
|
|
|
|
|
|
|
Low
|
1718
|
69.5
|
991
|
69.4
|
2,249
|
53.8
|
1,238
|
58.8
|
1,910
|
72.9
|
1,001
|
78.9
|
High
|
754
|
30.5
|
437
|
30.6
|
1,929
|
46.2
|
867
|
41.2
|
711
|
27.1
|
267
|
21.0
|
Place of residence
|
|
|
|
|
|
|
|
|
|
|
|
Urban
|
1254
|
50.7
|
653
|
45.7
|
1,201
|
28.7
|
558
|
26.5
|
1,393
|
53.1
|
594
|
46.8
|
Rural
|
1218
|
49.3
|
775
|
54.3
|
2,977
|
71.2
|
1,547
|
73.5
|
1,228
|
46.8
|
674
|
53.1
|
Source: (DHS) Ghana 2014; Rwanda 2015 and South Africa 2016. |
The prevalence of adolescent risky sexual behaviour
In the three countries surveyed as shown in figure 1 below, the rate of adolescents who reported to have engaged in multiple sexual partners ranges from 12% females and 13% males (Rwanda), 38% females and 30% males (Ghana), to 56% female 62% males (South Africa) as shown in Table 2 below. Those that started their first sexual encounter between ages 18 and 24 years old were highest among South Africa male adolescents at 22%, while the least is Rwandan female adolescents at 11%. In all the countries surveyed, those who have not had sex before their 24th birthday ranges from 75% Females (Rwanda), 49% females (Ghana), and 37% females (South Africa). Association with adolescent risky sexual behaviour and employment status was evident in all the three countries surveyed. The proportion of those without any employment to have been exposed to risky sexual behaviour ranges from 63% females and 45% males (Ghana), 43% females and 35% males (Rwanda), to 91% females and 84% males (South Africa).
In all the three countries surveyed as shown in figure 2, it was found that more than 50% of adolescent males and females with secondary education attainments had engaged in risky sexual behaviour compared to the 22% and 44% with a primary or fewer education attainments. Association of adolescent risky sexual behaviour with the neighbourhood poverty level ranges from 70% females and 74% males (Rwanda) to more than 50% for both genders in South Africa and Ghana. A similar pattern was observed for community media access as more than 60% of adolescent males and females with regular access to media in Rwanda have engaged in risky sexual behaviour. While 50% males and 47% females (South Africa) to 49% males and 69% females (Ghana) with regular access to media have engaged in risky sexual behaviour. For those in a high education community, the highest proportion was Rwanda with 46% females and 41% males. In all the countries surveyed, there was evidence of community characteristics influencing adolescents to have engaged in risky sexual behaviours.
Adolescent risky sexual behaviour predictors
The association between background characteristics and multiple sexual partnerships is presented in Table 2. The odds of having multiple sexual partners increased as age increased in all the three countries surveyed. After adjusting for all the other variables, female respondents in the 20 to 24 age category were significantly likely to have multiple sexual partners compared to those aged 15 to 19 years of Ghana (AOR = 3.72, 95% CI: 2.93), Rwanda (AOR = 2.77, 95% CI: 2.26-3.40) and South Africa (AOR = 5.19, 95% CI:4.25-6.33). Those with higher education attainments in Ghana and Rwanda were associated significantly at lower odds of engaging in multiple sexual partnerships at (AOR = 0.74, 95% CI: 0.44-1.24) and (AOR = 0.14, 95% CI: 0.04-0.46). Meanwhile, female adolescents from a household of 5 to 6 members in Ghana and Rwanda were 82% and 74% unlikely to have multiple sexual partners compared to those in South Africa with a 3% likelihood to have multiple sexual partners.
Table 2
Odds Ratios of Multiple sexual partners by selected Background Characteristic (Females)
|
Ghana
|
|
Rwanda
|
|
South Africa
|
|
|
Female
|
|
Female
|
|
Female
|
|
|
OR
|
aOR
|
OR
|
aOR
|
OR
|
aOR
|
Respondent age
|
|
|
|
|
|
15-19 RC
|
1
|
1
|
1
|
1
|
1
|
1
|
20-24
|
3.93*** (3.29-4.68)
|
3.7***(2.93-4.44)
|
2.89*** (2.38-3.50)
|
2.77*** 2.26-3.40)
|
6.31*** (5.29-7.54)
|
5.19*** (4.25-6.33)
|
Employment status
|
|
|
|
|
|
NO RC
|
1
|
1
|
1
|
1
|
1
|
1
|
Yes
|
1.96*** (1.65-2.32)
|
0.67 (0.40-1.09)
|
1.65*** (1.35-2.02)
|
0.98 (0.70-1.37)
|
3.06*** (2.21-4.25)
|
0.89 (0.41-1.93)
|
Respondent education attainment
|
|
|
|
Primary and less education RC
|
1
|
1
|
1
|
1
|
1
|
1
|
Secondary
|
1.32 (1.07-1.60)
|
1.17 (0.92-1.47)
|
0.88 (0.72-1.06)
|
0.83 (0.67-1.04)
|
1.79*** (1.29-2.49)
|
1.57* (1.09-2.26)
|
Higher
|
1.79 (1.16-2.75)
|
0.74(0.44-1.24)
|
0.30* (0.09-0.96)
|
0.14** (0.04-0.46)
|
3.90*** (2.43-6.28)
|
1.19 (0.68-2.10)
|
Household size
|
|
|
|
|
|
1 - 4 RC
|
1
|
1
|
1
|
1
|
1
|
1
|
5 - 6
|
0.69*** (0.58-0.850
|
0.82(0.66-1.02)
|
0.69** (0.54-0.88)
|
0.74* (0.58-0.96)
|
0.89 (0.73-1.08)
|
1.03 (0.83-1.27)
|
7 +
|
0.58*** (0.47-0.70)
|
0.65*** (0.52-0.80)
|
0.82 (0.65-1.02)
|
0.90 (0.71-1.15)
|
1.08 (0.89-1.29)
|
1.22 (0.99-1.49)
|
Source: (DHS) Ghana 2014; Rwanda 2015 and South Africa 2016 |
The association between background characteristics of male adolescents and multiple sexual partnerships is presented in Table 3. The odds of having multiple sexual behaviour increases as age increased in all three countries surveyed. After adjusting for all the other variables, male respondents in the 20 to 24 age category were significantly likely to have multiple sexual partners compared to those aged 15 to 19 years of Ghana (AOR = 4.58, 95% CI: 3.40-6.16), Rwanda (AOR = 2.72, 95% CI: 2.04-3.68) and South Africa (AOR = 4.56, 95% CI:3.33-6.24). Again, male adolescents with employment in South Africa were 57% less likely to engage in multiple sexual partnerships unlike those in Ghana and Rwanda with 63% and 60% likelihood. Education was found to be associated with multiple sexual partnerships among male adolescents in South Africa and Ghana at 2.26 and 1.28 odds significantly likely to have multiple sexual partners of those with secondary education attainment. Meanwhile, male adolescents from a household size of 5 to 6 in all the countries were unlikely to have multiple sexual partners compared to those from 1 to 4 household members.
Table 3
Odds Ratios Multiple sexual Partners by Selected Background Characteristics (Males)
|
Ghana
|
|
Rwanda
|
|
South Africa
|
|
Male
|
|
Male
|
|
Male
|
|
|
OR
|
aOR
|
OR
|
aOR
|
OR
|
aOR
|
Respondent age
|
|
|
|
|
|
15-19 RC
|
1
|
1
|
1
|
1
|
1
|
1
|
20-24
|
6.37*** (4.97-8.16)
|
4.58*** (3.40-6.16)
|
3.42*** (2.62-4.47)
|
2.72*** (2.04-3.63)
|
0.14*** (0.10-0.18)
|
4.56*** (3.33-6.24)
|
Employment status
|
|
|
|
|
|
No RC
|
1
|
1
|
1
|
1
|
1
|
1
|
yes
|
3.47*** (2.70-4.47)
|
2.63** (1.42-4.88)
|
1.98*** (1.47-2.67)
|
1.60 (0.60-4.25
|
3.76*** (2.55-5.54)
|
0.57 (0.25-1.28)
|
Respondent education attainment
|
|
|
|
Primary and less education RC
|
1
|
1
|
1
|
1
|
1
|
1
|
Secondary
|
1.58** (1.18-2.10)
|
1.28* (0.89-1.85)
|
1.00 (0.77-1.31)
|
0.82 (0.60-1.11)
|
2.86*** (2.04-3.98)
|
2.26*** (1.55-3.28)
|
Higher
|
4.09*** (2.29-7.32)
|
1.73* (0.83-3.60)
|
0.30* (0.09-3.76)
|
0.84 (0.39-1.78)
|
25.69*** (7.69-85.87)
|
5.88 (1.59-21.70)
|
Household size
|
|
|
|
|
|
1 - 4 RC
|
1
|
1
|
1
|
1
|
1
|
1
|
5 to 6
|
0.43*** (0.32-0.58)
|
0.67*(0.48-0.94)
|
0.63*** (0.46-0.87)
|
0.79 (0.56-1.10)
|
0.67* (0.50-0.99)
|
0.83 (0.59-1.14)
|
7 +
|
0.44*** (0.33-0.58)
|
0.68*(0.49-0.93)
|
0.83 (0.61-1.11)
|
1.04 (0.76-1.43)
|
0.76* (0.58-0.99)
|
0.87 (0.64-1.18)
|
Source: (DHS) Ghana 2014; Rwanda 2015 and South Africa 2016 |
The association between background characteristics of female adolescents and age at first sex is presented in Table 4. The odds of age at first sex among female adolescents increased as age increased in all the three countries surveyed. After adjusting for all the other variables, female respondents in the 20 to 24 aged category were significantly associated with age at first sex compared to those at ages 15 to 19 years of Ghana (AOR = 6.38, 95% CI: 5.07-8.04), Rwanda (AOR = 3.32, 95% CI: 0.84-3.87) and South Africa (AOR = 10.12, 95% CI:7.96-12.87). Education was found to be associated with age at first sex among female adolescents in South Africa and Ghana at 1.45 and 1.22 times odds among those with secondary education attainment, only those in Rwanda showed no association at the age at first sex. However, there was no association with age at first sex with those from a household of 5 to 6 members in Ghana. There was an association with age at first sex in Rwanda and South Africa among those from a household size of 5 to 6 members.
Table 4
Odds Ratios of Age at First Sex by Selected Background Characteristics (Females)
|
Ghana
|
|
Rwanda
|
|
South Africa
|
|
|
Female
|
|
Female
|
|
Female
|
|
|
OR
|
aOR
|
OR
|
aOR
|
OR
|
aOR
|
Respondent age
|
|
|
|
|
|
15-19 RC
|
1
|
1
|
1
|
1
|
1
|
1
|
20-24
|
6.38*** (5.26-7.73)
|
6.38*** (5.07-8.04)
|
3.27*** (2.83-3.78)
|
3.32*** (0.84-3.87)
|
11.69*** (9.44-14.67)
|
10.12*** (7.96-12.87)
|
Employment status
|
|
|
|
|
|
No RC
|
1
|
1
|
1
|
1
|
1
|
1
|
Yes
|
2.07 *** (1.75-2.44)
|
0.71 (0.42-1.20)
|
1.83*** (1.57-2.11)
|
1.05 (0.81-1.36)
|
4.60*** (3.07-6.90)
|
1.53 (0.62-3.78)
|
Respondent education attainment
|
|
|
|
Primary or less education RC
|
1
|
1
|
1
|
1
|
1
|
1
|
Secondary
|
1.44*** (1.19-1.74)
|
1.22 (0.97-1.53)
|
0.71*** (0.61-0.82)
|
0.66*** (0.56-0.78)
|
1.64** (1.18-2.27)
|
1.45* (0.99-2.11)
|
Higher
|
1.92** (1.25-2.97)
|
0.47 (0.28-0.82)
|
0.69 (0.39-1.23)
|
0.32*** (0.17-0.58)
|
3.89*** (2.36-6.39)
|
0.82 (0.44-1.54)
|
Household size
|
|
|
|
|
|
1 - 4 RC
|
1
|
1
|
1
|
1
|
1
|
1
|
5 - 6
|
0.67*** (0.56-0.81
|
0.82 (0.66-1.02)
|
0.92 (0.77-1.10)
|
1.01 (0.84-1.23)
|
0.87 (0.72-1.06)
|
1.01 (0.80-1.27)
|
7 +
|
0.53*** (1.27-1.66)
|
0.60*** (0.48-0.75)
|
0.96 (0.80-1.13)
|
1.11 (0.92-1.34)
|
1.13 (0.93-1.36)
|
1.30** (1.04-1.64)
|
Source: (DHS) Ghana 2014; Rwanda 2015 and South Africa 2016 |
The association between background characteristics of male adolescents and age at first sex is presented in Table 5. The table below shows that the odds of age at first sex among male adolescents increase as age increased in all the three countries surveyed. After adjusting for all the other variables, male respondents in the 20 to 24 age category were significantly associated with age at first sex compared to those aged 15 to 19 years of Ghana (AOR = 6.23, 95% CI: 4.67-8.32), Rwanda (AOR = 2.49, 95% CI: 2.03-3.06) and South Africa (AOR = 6.30, 95% CI: 4.37-9.10). Also, male adolescents with employment in Ghana and Rwanda were 85% and 32% more likely to be associated with age at first sex unlike those in South Africa with 84% unlikelihood to be associated with age at first sex than those without any employment. Education was found to be associated with age at first sex among male adolescents in South Africa and Ghana at 2.48 and 1.52 odds among those with secondary education attainment, only those in Rwanda showed no association at an age at first sex. There was no association with age at first sex with household size in all the three countries surveyed among male adolescents.
Table 5
Odds Ratios of Age at First Sex by Selected Background Characteristics (Males)
|
Ghana
|
|
Rwanda
|
|
South Africa
|
|
Male
|
|
Male
|
|
Male
|
|
|
OR
|
aOR
|
OR
|
aOR
|
OR
|
aOR
|
Respondent age
|
|
|
|
|
|
15-19 RC
|
1
|
1
|
1
|
1
|
1
|
1
|
20-24
|
8.53*** (6.68-10.88)
|
6.23***(4.67-8.32)
|
3.05*** (2.53-3.68)
|
2.49*** (2.03-3.06)
|
9.88*** (7.13-13.68)
|
6.30*** (4.37-9.10)
|
Employment status
|
|
|
|
|
|
No RC
|
1
|
1
|
1
|
1
|
1
|
1
|
Yes
|
2.94*** (2.35-3.67)
|
1.85* (1.05-3.27)
|
1.98*** (1.62-2.43)
|
1.32 (0.67-2.58)
|
5.11*** (3.17-8.24)
|
0.84 (0.34-2.08)
|
Respondent education attainment
|
|
|
|
Primary or less education RC
|
1
|
1
|
1
|
1
|
1
|
1
|
Secondary
|
1.86*** (1.43-2.42)
|
1.52* 1.07-2.15)
|
1.07 (0.89-1.30)
|
0.99*** (0.80-1.25)
|
3.17*** (2.27-4.40)
|
2.48*** (1.70-3.60)
|
Higher
|
5.66*** (3.06-10.45)
|
1.59 (0.74-3.40)
|
1.79* (1.03-3.09
|
0.94 (0.50-1.74)
|
63.16*** (8.53-46.70)
|
10.01** (1.28-84.40)
|
Household size
|
|
|
|
|
|
1 – 4 RC
|
1
|
1
|
1
|
1
|
1
|
1
|
5 – 6
|
0.40*** (0.31-0.53)
|
0.61** (0.45-0.84)
|
0.78* (0.62-0.98)
|
0.96 (0.75-1.22)
|
0.68** (0.50-0.92)
|
0.86 (0.61-1.20)
|
7 +
|
0.37*** (0.29-0.48)
|
0.54*** (0.40-0.74)
|
0.74 (0.59-0.92)
|
0.89 (0.70-1.13)
|
0.74* (0.50-0.99)
|
0.87 (0.63-1.20)
|
Source: (DHS) Ghana 2014; Rwanda 2015 and South Africa 2016 |
Table 6 presents the results of the multilevel logistics regression analysis of the risk of engaging in multiple sexual partnerships in all the countries surveyed among female adolescents. The results indicate that the test statistics was significant, thus it shows evidence that the between-neighbourhoods variance is non-zero, as was revealed on the variance partition coefficient (VPC) values. Therefore, the total variance in the risk of engaging in multiple sexual partners among female adolescents as a result of differences between neighbourhoods ranged from 5% (Ghana) to 10% (Rwanda) and 5% (South Africa). It was discovered that the variations decreased after controlling for individual (model 2) and neighbourhoods (model 3). More so, there were significant compositional effects as shown in Table 6. For instance, female adolescents living in high neighbourhood poverty significantly increased the odds of multiple sexual partnerships by 54% (South Africa) and 3% (Rwanda). There were 99% lower odds of engaging in multiple sexual partnerships among female adolescents living in high neighbourhood poverty in Ghana compared to those living in low neighbourhoods. Additionally, the results revealed that there was 14% and 1% (Ghana) for those without regular access to community media to have multiple sexual partners compared to those with no access. However, South Africa and Rwanda revealed lower odds of engaging in having multiple sexual partners among female adolescents with regular access to the community media.
Furthermore, the results showed strong significant effects with community occupation. For instance, female adolescents in agriculture increased the odds of having multiple sexual partners by 16% (South Africa), 3% (Rwanda) and 45% (Ghana). Again, community education increased the odds of engaging in multiple sexual partners among female adolescents by 53% (South Africa), to 4% (Ghana). Meanwhile, the higher the community education in Rwanda, the lower the odds of engaging in multiple sexual partners among female adolescents. The results from the three countries indicated that female adolescents living in rural areas had a higher level of exposure to engaging in multiple sexual partners in South Africa and Ghana, although the result was not significant. However, Rwanda had significantly lower odds of engaging in multiple sexual partners among female adolescents residing in rural areas compared to those residing in urban areas.
Table 6
Multilevel Logistic Regression analysis of multiple sexual partnerships among Female Adolescent
|
Model1: Null Model
|
|
|
Model 2: Individual
|
|
Model 3: Neighbourhood
|
|
Ghana
|
Rwanda
|
South Africa
|
Ghana
|
Rwanda
|
South Africa
|
Ghana
|
Rwanda
|
South Africa
|
Respondent age
|
|
|
|
|
|
|
|
|
15-19
|
|
|
|
1
|
1
|
1
|
|
|
|
20-24
|
|
|
|
4.08***
|
3.14***
|
6.42***
|
|
|
|
Employment status
|
|
|
|
|
|
|
|
|
No
|
|
|
|
1
|
1
|
1
|
|
|
|
Yes
|
|
|
|
1.54***
|
1.37
|
1.43*
|
|
|
|
Respondent education attainment
|
|
|
|
|
|
|
Primary and less education
|
|
1
|
1
|
1
|
|
|
|
Secondary
|
|
|
1.15
|
0.79*
|
1.57*
|
|
|
|
Higher
|
|
|
|
0.18
|
0.14**
|
1.46
|
|
|
|
Household size
|
|
|
|
|
|
|
|
|
1 - 4
|
|
|
|
1
|
1
|
1
|
|
|
|
5 - 6
|
|
|
|
0.84
|
0.73*
|
1.04
|
|
|
|
7 +
|
|
|
|
0.66**
|
0.91
|
1.24
|
|
|
|
Neighbourhood poverty
|
|
|
|
|
|
|
|
Low
|
|
|
|
|
|
|
1
|
1
|
1
|
High
|
|
|
|
|
|
|
0.99
|
1.03
|
1.54***
|
Community media access
|
|
|
|
|
|
|
|
No access
|
|
|
|
|
|
1
|
1
|
1
|
Not regular
|
|
|
|
|
|
1.14
|
0.86
|
0.72
|
Regularly
|
|
|
|
|
|
|
1.01
|
0.70*
|
0.84
|
Community occupation
|
|
|
|
|
|
|
|
Not working
|
|
|
|
|
|
1
|
1
|
1
|
Professionals
|
|
|
|
|
|
2.13***
|
2.01
|
1.47
|
Sales/unspecified
|
|
|
|
|
|
2.55***
|
2.38***
|
5.15*
|
Agriculture
|
|
|
|
|
|
1.45**
|
2.03***
|
11.16***
|
Manual
|
|
|
|
|
|
|
3.94***
|
3.39***
|
2.58***
|
Community education
|
|
|
|
|
|
|
|
Low
|
|
|
|
|
|
|
1
|
1
|
1
|
High
|
|
|
|
|
|
|
2.04***
|
0.95
|
3.53***
|
Place of residence
|
|
|
|
|
|
|
|
|
Urban
|
|
|
|
|
|
|
1
|
1
|
1
|
Rural
|
|
|
|
|
|
|
1.37**
|
0.43***
|
1.13
|
Random effects
|
|
Null
|
|
|
Individual
|
|
Neighbourhood
|
|
Community variance (SE)
|
0.018756
|
0.60848
|
0.410184
|
0.6944607
|
0.711216
|
0.419383
|
0.699517
|
0.534234
|
0.460199
|
VPC=ICC (%)
|
0.05
|
0.10
|
0.05
|
0.13
|
0.13
|
0.05
|
0.13
|
0.08
|
0.06
|
Explained variation PCV (%)
|
Ref
|
Ref.
|
Ref.
|
-9.65
|
-31.74
|
-4.31
|
-11.05
|
21.09
|
-24.31
|
Log-Likelihood
|
-1792.84
|
-1483.68
|
-1792.84
|
-1479.999
|
-1395.99
|
-1549.95
|
-1549.37
|
-1433.16
|
-1674.63
|
Model fit statistics
|
|
|
|
|
|
|
|
|
AIC
|
3589.682
|
2971.352
|
3589.682
|
2975.997
|
2807.974
|
3115.891
|
3120.745
|
2888.313
|
3371.264
|
BIC
|
3601.424
|
2984.027
|
3601.424
|
3022.486
|
2858.642
|
3162.861
|
3184.7
|
2957.987
|
3435.848
|
Source: (DHS) Ghana 2014; Rwanda 2015 and South Africa 2016 |
The results presented in Table 7 reveals the risk of engaging in multiple sexual partnerships among male adolescents in all the countries surveyed. The results indicate that the test statistics was significant, hence, it indicates evidence that the between-neighbourhoods variance is non-zero, as was revealed on the variance partition coefficient (VPC) values. Therefore, the total variance in the risk of engaging in multiple sexual partners among male adolescents as a result of differences that existed between neighbourhoods ranged from 15% (Ghana) to 11% (Rwanda) and 14% (South Africa). It was discovered that the variations decreased after controlling for individual (model 2) and neighbourhoods (model 3) characteristics. More so, there were significant compositional effects as observed in Table 7 below. For example, male adolescents living in high neighbourhood poverty significantly increased the odds of multiple sexual partnerships by 45% (South Africa), to 55% (Rwanda) and 45% (Ghana) compared to those living in low neighbourhoods. Additionally, the results revealed community media access significantly increased the odds of multiple sexual partnerships among male adolescents in Ghana and Rwanda among those with regular access. Also, there was a 63% (Ghana), to 48% (Rwanda) and 33% increase in the odds among male adolescents without regular access to community media, though not significant. Furthermore, the results showed strong significant effects with community occupation. For instance, male adolescents in the category of professionals significantly increased the odds of having multiple sexual partners by 60% (South Africa), 23% (Rwanda) and 97% (Ghana).
Again, community education significantly increased the odds of engaging in multiple sexual partners among male adolescents by 23% (South Africa), to 20% (Ghana). Meanwhile, the higher the community education in Rwanda, the lower the odds of engaging in multiple sexual partners among male adolescents. The results from the three countries indicated that male adolescents living in rural areas had a higher level of exposure to engaging in multiple sexual partners in South Africa, Rwanda and Ghana, although the result was not significant in South Africa.
Table 7
Multilevel Logistic regression analysis of multiple sexual partnerships among Male Adolescent
|
Model1: Null Model
|
|
Model 2: Individual
|
Model 3: Neighbourhood
|
|
Ghana
|
Rwanda
|
South Africa
|
Ghana
|
Rwanda
|
South Africa
|
Ghana
|
Rwanda
|
South Africa
|
Respondent age
|
|
|
|
|
|
|
|
|
15-19
|
|
|
|
1
|
1
|
1
|
|
|
|
20-24
|
|
|
|
5.80***
|
3.09***
|
6.59***
|
|
|
|
Employment status
|
|
|
|
|
|
|
|
|
No
|
|
|
|
1
|
1
|
1
|
|
|
|
Yes
|
|
|
|
3.28***
|
1.69**
|
1.74*
|
|
|
|
Respondent education attainment
|
|
|
|
|
|
|
Primary and less education
|
|
1
|
1
|
1
|
|
|
|
Secondary
|
|
|
1.64
|
1.09
|
2.63***
|
|
|
|
Higher
|
|
|
|
2.22*
|
1.31
|
9.08***
|
|
|
|
Household size
|
|
|
|
|
|
|
|
|
1 - 4
|
|
|
|
1
|
1
|
1
|
|
|
|
5 - 6
|
|
|
|
0.61
|
0.75
|
0.67*
|
|
|
|
7 +
|
|
|
|
0.60*
|
1.04
|
0.76*
|
|
|
|
Neighbourhood poverty
|
|
|
|
|
|
|
|
Low
|
|
|
|
|
|
|
1
|
1
|
1
|
High
|
|
|
|
|
|
|
0.45***
|
0.55**
|
1.45*
|
Community media access
|
|
|
|
|
|
|
|
No access
|
|
|
|
|
|
1
|
1
|
1
|
Not regular
|
|
|
|
|
|
1.63
|
1.48
|
1.33
|
Regularly
|
|
|
|
|
|
1.90*
|
2.86**
|
1.39
|
Community occupation
|
|
|
|
|
|
|
|
Not working
|
|
|
|
|
|
1
|
1
|
1
|
Professionals
|
|
|
|
|
|
3.97***
|
3.23*
|
4.60*
|
Sales/unspecified
|
|
|
|
|
7.03***
|
2.64***
|
0.92
|
Agriculture
|
|
|
|
|
|
2.95***
|
2.11***
|
1.7
|
Manual
|
|
|
|
|
|
|
7.68***
|
2.81***
|
6.33***
|
Community education
|
|
|
|
|
|
|
|
Low
|
|
|
|
|
|
|
1
|
1
|
1
|
High
|
|
|
|
|
|
|
2.20***
|
0.98
|
5.23***
|
Place of residence
|
|
|
|
|
|
|
|
|
urban
|
|
|
|
|
|
|
1
|
1
|
1
|
Rural
|
|
|
|
|
|
|
1.55*
|
0.55***
|
1.03
|
Random effects
|
|
Null
|
|
|
Individual
|
|
|
Neighbourhood
|
|
Community variance (SE)
|
0.749914
|
0.633636
|
0.744414
|
0.821268
|
0.551064
|
0.81616
|
0.68273
|
0.387579
|
0.749803
|
VPC=ICC (%)
|
0.15
|
0.11
|
0.14
|
0.17
|
0.08
|
0.17
|
0.12
|
0.04
|
0.15
|
Explained variation PCV (%)
|
Ref.
|
Ref.
|
Ref.
|
-16.54
|
22.31
|
-16.80
|
14.99
|
59.85
|
-1.24
|
Log-Likelihood
|
-865.326
|
-812.999
|
-835.986
|
-709.142
|
-763.781
|
-703.161
|
-758.634
|
-766.76
|
-750.068
|
Model fit statistics
|
|
|
|
|
|
|
|
|
AIC
|
1734.651
|
1629.997
|
1675.972
|
1432.284
|
1543.563
|
1420.322
|
1539.268
|
1555.519
|
1522.136
|
BIC
|
1745.179
|
1641.301
|
1686.263
|
1469.127
|
1588.745
|
1456.339
|
1597.157
|
1617.656
|
1578.734
|
Source: (DHS) Ghana 2014; Rwanda 2015 and South Africa 2016 |
In Table 8 below, the results of age at first sex in all the countries surveyed among female adolescents is presented. The test of statistics was significant, as the result of variance partition coefficient (VPC) values indicated that the between-neighbourhoods variance is non-zero. Therefore, the total variance in age at first sex among female adolescents as a result of differences that existed between neighbourhoods ranged from 15% (Ghana) to 11% (Rwanda) and 14% (South Africa). After controlling for individual (model 2) and neighbourhoods (model 3) characteristics, the variations decreased.
The results indicate that there were significant compositional effects as shown in the results displayed in Table 8 below. For instance, adolescent females living in high neighbourhood poverty in South Africa significantly increased the age of first sex at 81%. In addition, there was an increased odds of 8% in Ghana, though not significant, compared to female adolescents in Rwanda with a lower odds of age at first sex at 98%.
Among all the countries, results revealed that community media access significantly reduced the odds of age at first sex, except in Ghana where female adolescents had an increased likelihood of age at first sex among those without regular access to community media, though not significant. Furthermore, the results showed strong significant effects with community occupation. For instance, female adolescents in all the categories of occupations significantly increased the odds of age at first sex. Again, community education significantly increased the odds of age at first sex among female adolescents by 50% (South Africa), to 46% (Ghana). Meanwhile, the higher the community education in Rwanda, the lower the odds of age at first sex among female adolescents. The results from the three countries indicated that female adolescents living in rural areas had a higher level of exposure to age at first sex in South Africa, Rwanda and Ghana, although the results were not significant in South Africa.
Table 8
Multilevel Logistic regression analysis of Age at First Sex among Female Adolescent
|
|
Model 1: Null
|
|
Model 2: Individual
|
Model 3: Neighbourhood
|
|
Ghana
|
Rwanda
|
South Africa
|
Ghana
|
Rwanda
|
South Africa
|
Ghana
|
Rwanda
|
South Africa
|
Respondent age
|
|
|
|
|
|
|
|
|
15-19
|
|
|
|
1
|
1
|
1
|
|
|
|
20-24
|
|
|
|
7.96***
|
3.59***
|
13.47***
|
|
|
|
Employment status
|
|
|
|
|
|
|
|
No
|
|
|
|
1
|
1
|
1
|
|
|
|
Yes
|
|
|
|
1.51***
|
1.47***
|
1.77*
|
|
|
|
Respondent education attainment
|
|
|
|
|
|
|
Primary and less education
|
1
|
1
|
1
|
|
|
|
Secondary
|
|
|
1.14
|
0.62***
|
1.43
|
|
|
|
Higher
|
|
|
|
0.41***
|
0.32***
|
0.99
|
|
|
|
Household size
|
|
|
|
|
|
|
|
|
1 - 4
|
|
|
|
1
|
1
|
1
|
|
|
|
5 - 6
|
|
|
|
0.85
|
1.02
|
1.06
|
|
|
|
7 +
|
|
|
|
0.62***
|
1.09
|
1.38
|
|
|
|
Neighbourhood poverty
|
|
|
|
|
|
|
|
Low
|
|
|
|
|
|
|
1
|
1
|
1
|
High
|
|
|
|
|
|
|
1.08
|
0.98
|
1.81***
|
Community media access
|
|
|
|
|
|
|
|
No access
|
|
|
|
|
|
1
|
1
|
1
|
Not regular
|
|
|
|
|
|
1.18
|
0.85
|
0.74*
|
Regularly
|
|
|
|
|
|
1.03
|
0.71
|
0.81*
|
Community occupation
|
|
|
|
|
|
|
|
Not working
|
|
|
|
|
|
1
|
1
|
1
|
Professionals
|
|
|
|
|
|
2.13***
|
2.09*
|
1.80*
|
Sales/unspecified
|
|
|
|
|
2.72***
|
2.53***
|
0.11
|
Agriculture
|
|
|
|
|
|
1.36*
|
2.19***
|
3.73***
|
Manual
|
|
|
|
|
|
|
4.97***
|
2.50***
|
8.24
|
Community education
|
|
|
|
|
|
|
|
Low
|
|
|
|
|
|
|
1
|
1
|
|
High
|
|
|
|
|
|
|
2.63***
|
0.46***
|
4.50***
|
Place of residence
|
|
|
|
|
|
|
|
Urban
|
|
|
|
|
|
|
1
|
1
|
1
|
Rural
|
|
|
|
|
|
|
1.41*
|
0.78**
|
1.12
|
Random effects
|
|
Null
|
|
|
Individual
|
|
Neighbourhood
|
|
Community variance (SE)
|
0.42589
|
0.1916
|
0.27593
|
0.52216
|
0.29283
|
0.37927
|
0.48958
|
0.15424
|
0.33546
|
VPC=ICC (%)
|
0.11
|
0.06
|
0.08
|
0.14
|
0.08
|
0.10
|
0.13
|
0.04
|
0.09
|
Explained variation PCV (%)
|
Ref
|
Ref.
|
Ref.
|
-19.51
|
-48.51
|
-33.58
|
-13.02
|
18.62
|
-19.58
|
Log-Likelihood
|
-1688.7
|
-2353.9
|
-1720.3
|
-1451.7
|
-2172.5
|
-1366.3
|
-1588.5
|
-2259.2
|
-1575.5
|
Model fit statistics
|
|
|
|
|
|
|
|
AIC
|
3381.4
|
4711.84
|
3444.61
|
2919.32
|
4361.07
|
2748.68
|
3198.9
|
4540.43
|
3170.95
|
BIC
|
3393.03
|
4724.52
|
3456.36
|
2965.81
|
4411.74
|
2795.65
|
3262.84
|
4610.1
|
3229.61
|
Source: (DHS) Ghana 2014; Rwanda 2015 and South Africa 2016 |
The results of age at first sex in all the countries surveyed among male adolescents are presented in Table 9 below. The test of statistics was significant, as the result of variance partition coefficient (VPC) values indicated that the between-neighbourhoods variance is non-zero. Therefore, the total variance in age at first sex among male adolescents as a result of differences that existed between neighbourhoods ranged from 14% (Ghana) to 12% (Rwanda) and 17% (South Africa). In addition, after controlling for individual (model 2) and neighbourhoods (model 3) characteristics, the variations decreased.
The results further revealed that there were significant compositional effects. For example, adolescent males living in high neighbourhood poverty in South Africa significantly increased the age of first sex by 26%. The results indicate that there was no association in age at first sex in Ghana and Rwanda among females in high neighbourhood poverty compared to those in low neighbourhood poverty. In all the countries, results revealed that community media access significantly increased the odds of age at first sex among those that regularly and not regularly accessed community media, except in Ghana among male adolescents without regular access to community media.
Furthermore, the results showed strong significant effects with community occupation. For instance, male adolescents in all the categories of occupation significantly increased the odds of age at first sex. Again, community education significantly increased the odds of age at first sex among male adolescents by 50% (South Africa), to 46% (Ghana). Meanwhile, the higher the community education in Rwanda, the higher the odds of age at first sex among male adolescents, although not significant. The results from the three countries indicated that male adolescents living in rural areas had a higher level of exposure to age at first sex in South Africa and Ghana, although the results were insignificant in South Africa compared to those in Rwanda with 66% significant lower odds of age at first sex.
Table 9
Multilevel Logistic analysis of Age at First Sex among Male Adolescent
|
|
Model 1: Null
|
|
Model 2: Individual
|
Model 3: Neighbourhood
|
|
Ghana
|
Rwanda
|
South Africa
|
Ghana
|
Rwanda
|
South Africa
|
Ghana
|
Rwanda
|
South Africa
|
Respondent age
|
|
|
|
|
|
|
|
|
15-19
|
|
|
|
1
|
1
|
1
|
|
|
|
20-24
|
|
|
|
8.41***
|
2.94***
|
10.07***
|
|
|
Employment status
|
|
|
|
|
|
|
|
No
|
|
|
|
1
|
1
|
1
|
|
|
|
Yes
|
|
|
|
2.70***
|
1.84***
|
2.24
|
|
|
|
Respondent education attainment
|
|
|
|
|
|
|
Primary and less education
|
1
|
1
|
1
|
|
|
|
Secondary
|
|
|
1.98***
|
1.15
|
3.34***
|
|
|
|
Higher
|
|
|
|
2.27*
|
1.27
|
18.24
|
|
|
|
Household size
|
|
|
|
|
|
|
|
|
1 - 4
|
|
|
|
1
|
1
|
1
|
|
|
|
5 - 6
|
|
|
|
0.56***
|
0.94
|
0.81
|
|
|
|
7 +
|
|
|
|
0.48***
|
0.88
|
0.88
|
|
|
|
Neighbourhood poverty
|
|
|
|
|
|
|
|
Low
|
|
|
|
|
|
|
1
|
1
|
1
|
High
|
|
|
|
|
|
|
0.56***
|
0.7
|
1.26
|
Community media access
|
|
|
|
|
|
|
|
No access
|
|
|
|
|
|
1
|
1
|
1
|
Not regular
|
|
|
|
|
|
0.99
|
1.46
|
1.53*
|
Regularly
|
|
|
|
|
|
1.28
|
2.29***
|
1.39
|
Community occupation
|
|
|
|
|
|
|
|
Not working
|
|
|
|
|
|
1
|
1
|
1
|
Professionals
|
|
|
|
|
|
4.12***
|
2.93**
|
11.87*
|
Sales/unspecified
|
|
|
|
|
6.52***
|
3.14***
|
1.24
|
Agriculture
|
|
|
|
|
|
2.83***
|
2.19***
|
2.32*
|
Manual
|
|
|
|
|
|
|
6.99***
|
3.68***
|
7.66***
|
Community education
|
|
|
|
|
|
|
|
Low
|
|
|
|
|
|
|
1
|
1
|
1
|
High
|
|
|
|
|
|
|
2.83***
|
1.16
|
6.44***
|
Place of residence
|
|
|
|
|
|
|
|
Urban
|
|
|
|
|
|
|
1
|
1
|
1
|
Rural
|
|
|
|
|
|
|
1.11
|
0.66*
|
1.09
|
Random effects
|
|
Null
|
|
|
Individual
|
|
Neighbourhood
|
|
Community variance (SE)
|
0.72849
|
0.44826
|
0.66001
|
0.81416
|
0.45336
|
1.04597
|
0.68178
|
0.36022
|
0.75527
|
VPC=ICC (%)
|
0.14
|
0.12
|
0.17
|
0.17
|
0.12
|
0.24
|
0.12
|
0.10
|
0.19
|
Explained variation PCV (%)
|
Ref.
|
Ref.
|
Ref.
|
-20.73
|
-1.00
|
-44.37
|
10.87
|
-82.30
|
-11.74
|
Log-Likelihood
|
-955.39
|
-1326.9
|
-777.04
|
-745.58
|
-1241.5
|
-625.78
|
-837.31
|
-1256.4
|
-692.81
|
Model fit statistics
|
|
|
|
|
|
|
|
AIC
|
1914.77
|
2657.83
|
1558.08
|
1505.16
|
2499
|
1265.55
|
1696.62
|
2534.84
|
1407.62
|
BIC
|
1925.3
|
2669.14
|
1568.37
|
1542
|
2544.17
|
1301.57
|
1754.51
|
2596.98
|
1464.22
|
Source: (DHS) Ghana 2014; Rwanda 2015 and South Africa 2016 |