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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Trends in age at first sex in Uganda: evidence from Demographic and
Health Survey data and longitudinal cohorts in Masaka and Rakai</title>
<author><name sortKey="Slaymaker, E" sort="Slaymaker, E" uniqKey="Slaymaker E" first="E" last="Slaymaker">E. Slaymaker</name>
<affiliation><nlm:aff id="aff1"><addr-line>Centre for Population Studies, London School of Hygiene and Tropical Medicine, London, UK</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Bwanika, J B" sort="Bwanika, J B" uniqKey="Bwanika J" first="J B" last="Bwanika">J B Bwanika</name>
<affiliation><nlm:aff id="aff2"><addr-line>Rakai Health Sciences Program, Kalisizo, Rakai, Uganda</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Kasamba, I" sort="Kasamba, I" uniqKey="Kasamba I" first="I" last="Kasamba">I. Kasamba</name>
<affiliation><nlm:aff id="aff3"><addr-line>MRC/UVRI Research Unit on AIDS, Entebbe, Uganda</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Lutalo, T" sort="Lutalo, T" uniqKey="Lutalo T" first="T" last="Lutalo">T. Lutalo</name>
<affiliation><nlm:aff id="aff2"><addr-line>Rakai Health Sciences Program, Kalisizo, Rakai, Uganda</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Maher, D" sort="Maher, D" uniqKey="Maher D" first="D" last="Maher">D. Maher</name>
<affiliation><nlm:aff id="aff3"><addr-line>MRC/UVRI Research Unit on AIDS, Entebbe, Uganda</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Todd, J" sort="Todd, J" uniqKey="Todd J" first="J" last="Todd">J. Todd</name>
<affiliation><nlm:aff id="aff3"><addr-line>MRC/UVRI Research Unit on AIDS, Entebbe, Uganda</addr-line>
</nlm:aff>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PMC</idno>
<idno type="pmid">19307335</idno>
<idno type="pmc">2654114</idno>
<idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2654114</idno>
<idno type="RBID">PMC:2654114</idno>
<idno type="doi">10.1136/sti.2008.034009</idno>
<date when="2009">2009</date>
<idno type="wicri:Area/Pmc/Corpus">002C78</idno>
<idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">002C78</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Trends in age at first sex in Uganda: evidence from Demographic and
Health Survey data and longitudinal cohorts in Masaka and Rakai</title>
<author><name sortKey="Slaymaker, E" sort="Slaymaker, E" uniqKey="Slaymaker E" first="E" last="Slaymaker">E. Slaymaker</name>
<affiliation><nlm:aff id="aff1"><addr-line>Centre for Population Studies, London School of Hygiene and Tropical Medicine, London, UK</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Bwanika, J B" sort="Bwanika, J B" uniqKey="Bwanika J" first="J B" last="Bwanika">J B Bwanika</name>
<affiliation><nlm:aff id="aff2"><addr-line>Rakai Health Sciences Program, Kalisizo, Rakai, Uganda</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Kasamba, I" sort="Kasamba, I" uniqKey="Kasamba I" first="I" last="Kasamba">I. Kasamba</name>
<affiliation><nlm:aff id="aff3"><addr-line>MRC/UVRI Research Unit on AIDS, Entebbe, Uganda</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Lutalo, T" sort="Lutalo, T" uniqKey="Lutalo T" first="T" last="Lutalo">T. Lutalo</name>
<affiliation><nlm:aff id="aff2"><addr-line>Rakai Health Sciences Program, Kalisizo, Rakai, Uganda</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Maher, D" sort="Maher, D" uniqKey="Maher D" first="D" last="Maher">D. Maher</name>
<affiliation><nlm:aff id="aff3"><addr-line>MRC/UVRI Research Unit on AIDS, Entebbe, Uganda</addr-line>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Todd, J" sort="Todd, J" uniqKey="Todd J" first="J" last="Todd">J. Todd</name>
<affiliation><nlm:aff id="aff3"><addr-line>MRC/UVRI Research Unit on AIDS, Entebbe, Uganda</addr-line>
</nlm:aff>
</affiliation>
</author>
</analytic>
<series><title level="j">Sexually Transmitted Infections</title>
<idno type="ISSN">1368-4973</idno>
<idno type="eISSN">1472-3263</idno>
<imprint><date when="2009">2009</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass></textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en"><sec><title>Objectives:</title>
<p>To derive the best possible estimates of trends in age at first sex
(AFS) among successive cohorts of Ugandan men and women
based on all the data available from the Demographic and Health Surveys
(DHS) and cohort studies in Masaka and Rakai
districts.</p>
</sec>
<sec><title>Methods:</title>
<p>The datasets from the DHS, Masaka cohort and Rakai cohort were analysed
separately. Survival analysis methods were used to estimate median AFS for
men and women born in the 1950s–1980s and to compute hazard
ratios for first sex, comparing later cohorts with earlier cohorts.</p>
</sec>
<sec><title>Results:</title>
<p>The DHS and Masaka data showed an increase in AFS in women in the more recent
birth cohorts compared with those born before 1970, but this was less
apparent in the Rakai data. Successive male cohorts in Masaka appeared first
to have an increased AFS which subsequently decreased, a trend that was also
apparent (but not significant) in the DHS data. Younger
men in Rakai had an earlier AFS than those born before 1980.</p>
</sec>
<sec><title>Conclusions:</title>
<p>Women in Uganda who were born after 1970 have, on average, had sex at a later
age than those born earlier. For men, AFS has not changed consistently over
the period in question. Differences between Masaka and Rakai may reflect
socioeconomic differences. Most of the change in AFS occurred too late to
have contributed to the initial decline in the incidence of HIV.</p>
</sec>
</div>
</front>
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</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Dickson, N" uniqKey="Dickson N">N Dickson</name>
</author>
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<biblStruct><analytic><author><name sortKey="Kamali, A" uniqKey="Kamali A">A Kamali</name>
</author>
<author><name sortKey="Carpenter, Lm" uniqKey="Carpenter L">LM Carpenter</name>
</author>
<author><name sortKey="Whitworth, Jag" uniqKey="Whitworth J">JAG Whitworth</name>
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<biblStruct><analytic><author><name sortKey="Kirungi, Wl" uniqKey="Kirungi W">WL Kirungi</name>
</author>
<author><name sortKey="Musinguzi, J" uniqKey="Musinguzi J">J Musinguzi</name>
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<author><name sortKey="Madraa, E" uniqKey="Madraa E">E Madraa</name>
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</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Bessinger, R" uniqKey="Bessinger R">R Bessinger</name>
</author>
<author><name sortKey="Akwara, P" uniqKey="Akwara P">P Akwara</name>
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<biblStruct><analytic><author><name sortKey="Green, E" uniqKey="Green E">E Green</name>
</author>
<author><name sortKey="Halperin, D" uniqKey="Halperin D">D Halperin</name>
</author>
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<biblStruct><analytic><author><name sortKey="Singh, S" uniqKey="Singh S">S Singh</name>
</author>
<author><name sortKey="Darroch, Je" uniqKey="Darroch J">JE Darroch</name>
</author>
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<biblStruct><analytic><author><name sortKey="Parkhurst, J" uniqKey="Parkhurst J">J Parkhurst</name>
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<biblStruct><analytic><author><name sortKey="Wringe, A" uniqKey="Wringe A">A Wringe</name>
</author>
<author><name sortKey="Cremin, I" uniqKey="Cremin I">I Cremin</name>
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<author><name sortKey="Todd, J" uniqKey="Todd J">J Todd</name>
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</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Mulder, D" uniqKey="Mulder D">D Mulder</name>
</author>
<author><name sortKey="Nunn, A" uniqKey="Nunn A">A Nunn</name>
</author>
<author><name sortKey="Wagner, H" uniqKey="Wagner H">H Wagner</name>
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</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Wawer, M" uniqKey="Wawer M">M Wawer</name>
</author>
<author><name sortKey="Gray, R" uniqKey="Gray R">R Gray</name>
</author>
<author><name sortKey="Sewankambo, N" uniqKey="Sewankambo N">N Sewankambo</name>
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</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Wawer, M" uniqKey="Wawer M">M Wawer</name>
</author>
<author><name sortKey="Sewankambo, N" uniqKey="Sewankambo N">N Sewankambo</name>
</author>
<author><name sortKey="Serwadda, D" uniqKey="Serwadda D">D Serwadda</name>
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</analytic>
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<biblStruct><analytic><author><name sortKey="Royston, P" uniqKey="Royston P">P Royston</name>
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<biblStruct><analytic><author><name sortKey=" Aba, B" uniqKey=" Aba B">B Żaba</name>
</author>
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<author><name sortKey="Slaymaker, E" uniqKey="Slaymaker E">E Slaymaker</name>
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</analytic>
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<author><name sortKey="Kagaayi, J" uniqKey="Kagaayi J">J Kagaayi</name>
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<author><name sortKey="Gray, R" uniqKey="Gray R">R Gray</name>
</author>
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</biblStruct>
</listBibl>
</div1>
</back>
</TEI>
<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Sex Transm Infect</journal-id>
<journal-id journal-id-type="publisher-id">sti</journal-id>
<journal-title-group><journal-title>Sexually Transmitted Infections</journal-title>
</journal-title-group>
<issn pub-type="ppub">1368-4973</issn>
<issn pub-type="epub">1472-3263</issn>
<publisher><publisher-name>BMJ Publishing Group</publisher-name>
<publisher-loc>BMA House, Tavistock Square, London, WC1H 9JR</publisher-loc>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">19307335</article-id>
<article-id pub-id-type="pmc">2654114</article-id>
<article-id pub-id-type="publisher-id">st34009</article-id>
<article-id pub-id-type="doi">10.1136/sti.2008.034009</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Supplement</subject>
</subj-group>
<subj-group subj-group-type="hwp-journal-coll"><subject>1506</subject>
</subj-group>
</article-categories>
<title-group><article-title>Trends in age at first sex in Uganda: evidence from Demographic and
Health Survey data and longitudinal cohorts in Masaka and Rakai</article-title>
<alt-title alt-title-type="running-head">Supplement</alt-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Slaymaker</surname>
<given-names>E</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Bwanika</surname>
<given-names>J B</given-names>
</name>
<xref ref-type="aff" rid="aff2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Kasamba</surname>
<given-names>I</given-names>
</name>
<xref ref-type="aff" rid="aff3">3</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Lutalo</surname>
<given-names>T</given-names>
</name>
<xref ref-type="aff" rid="aff2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Maher</surname>
<given-names>D</given-names>
</name>
<xref ref-type="aff" rid="aff3">3</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Todd</surname>
<given-names>J</given-names>
</name>
<xref ref-type="aff" rid="aff3">3</xref>
</contrib>
</contrib-group>
<aff id="aff1"><label>1</label>
<addr-line>Centre for Population Studies, London School of Hygiene and Tropical Medicine, London, UK</addr-line>
</aff>
<aff id="aff2"><label>2</label>
<addr-line>Rakai Health Sciences Program, Kalisizo, Rakai, Uganda</addr-line>
</aff>
<aff id="aff3"><label>3</label>
<addr-line>MRC/UVRI Research Unit on AIDS, Entebbe, Uganda</addr-line>
</aff>
<author-notes><corresp>Correspondence to: Ms E Slaymaker, Centre for Population Studies, London
School of Hygiene and Tropical Medicine, 49–51 Bedford Square, London
WC1B 3DP, UK; <email>emma.slaymaker@lshtm.ac.uk</email>
</corresp>
<fn fn-type="other"><p><bold>Contributors:</bold>
ES planned the analyses and analysed the DHS data.
JT oversaw the analyses. JT, IK and DM analysed the Masaka data. TL and JBB
analysed the Rakai data. All authors reviewed the results and wrote the
paper.</p>
</fn>
<fn><p>A figure is published online only at <ext-link ext-link-type="uri" xlink:href="http://sti.bmj.com/content/vol85/issueSupplI">http://sti.bmj.com/content/vol85/issueSupplI</ext-link>
</p>
</fn>
</author-notes>
<pub-date pub-type="collection"><year>2009</year>
</pub-date>
<pub-date pub-type="ppub"><month>4</month>
<year>2009</year>
</pub-date>
<pub-date pub-type="epub"><day>13</day>
<month>3</month>
<year>2009</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>13</day>
<month>3</month>
<year>2009</year>
</pub-date>
<pmc-comment> PMC Release delay is 0 months and 0 days and was based on the
. </pmc-comment>
<volume>85</volume>
<issue>Suppl_1</issue>
<issue-title>Trends in sexual behaviour and marriage in sub-Saharan Africa</issue-title>
<fpage>i12</fpage>
<lpage>i19</lpage>
<history><date date-type="accepted"><day>20</day>
<month>1</month>
<year>2009</year>
</date>
</history>
<permissions><copyright-statement>© Slaymaker et al 2009</copyright-statement>
<copyright-year>2009</copyright-year>
<license license-type="openaccess" xlink:href="http://creativecommons.org/licenses/by/2.0/"><license-p>This is an open-access article distributed under the terms of the Creative
Commons Attribution Non-commercial License, which permits unrestricted use,
distribution, and reproduction in any medium, provided the original work is
properly cited.</license-p>
</license>
</permissions>
<abstract><sec><title>Objectives:</title>
<p>To derive the best possible estimates of trends in age at first sex
(AFS) among successive cohorts of Ugandan men and women
based on all the data available from the Demographic and Health Surveys
(DHS) and cohort studies in Masaka and Rakai
districts.</p>
</sec>
<sec><title>Methods:</title>
<p>The datasets from the DHS, Masaka cohort and Rakai cohort were analysed
separately. Survival analysis methods were used to estimate median AFS for
men and women born in the 1950s–1980s and to compute hazard
ratios for first sex, comparing later cohorts with earlier cohorts.</p>
</sec>
<sec><title>Results:</title>
<p>The DHS and Masaka data showed an increase in AFS in women in the more recent
birth cohorts compared with those born before 1970, but this was less
apparent in the Rakai data. Successive male cohorts in Masaka appeared first
to have an increased AFS which subsequently decreased, a trend that was also
apparent (but not significant) in the DHS data. Younger
men in Rakai had an earlier AFS than those born before 1980.</p>
</sec>
<sec><title>Conclusions:</title>
<p>Women in Uganda who were born after 1970 have, on average, had sex at a later
age than those born earlier. For men, AFS has not changed consistently over
the period in question. Differences between Masaka and Rakai may reflect
socioeconomic differences. Most of the change in AFS occurred too late to
have contributed to the initial decline in the incidence of HIV.</p>
</sec>
</abstract>
</article-meta>
</front>
<body><p>Although not a strategy that can be maintained throughout a lifetime, avoidance of
sexual intercourse is a reliable way to avoid contracting most sexually transmitted
infections and of preventing unwanted conceptions. Abstinence has been a key
component of many HIV prevention programmes in Africa and elsewhere.<xref ref-type="bibr" rid="b1">1</xref>
<sup>–</sup>
<xref ref-type="bibr" rid="b3">3</xref>
Abstinence usually means encouraging young people to delay
their sexual debut with the intention of reducing their exposure to sex and sexual
partners before committing to a stable and hopefully long-lasting partner. For HIV
prevention, implicit in this message is that this permanent partner is uninfected,
or at least less likely to be infected than other more casual partners.</p>
<p>There is considerable interest in measuring levels and trends in the key behaviours
tackled by many HIV prevention programmes: abstinence, number of partners and condom
use. Age at first sex (AFS) is a key indicator for measuring behaviour change in HIV
prevention programmes.<xref ref-type="bibr" rid="b1">1</xref>
<xref ref-type="bibr" rid="b4">4</xref>
<xref ref-type="bibr" rid="b5">5</xref>
In many developing countries, AFS and age at
first marriage (AFM) have occurred at older ages in recent years compared with
40–50 years ago.<xref ref-type="bibr" rid="b6">6</xref>
<xref ref-type="bibr" rid="b7">7</xref>
The reasons for these changes are complex,
but there are clear links between development and delayed AFS. It is also clear that
behaviour change does not occur in isolation as risk behaviour is unlikely to change
unless the social context is supportive of change. The timing of first sex is a
product of agency and opportunity. Individuals may have limited autonomy to delay
sexual debut if their first experience of sex is through coercive sex or rape.<xref ref-type="bibr" rid="b8">8</xref>
<sup>–</sup>
<xref ref-type="bibr" rid="b10">10</xref>
</p>
<p>Uganda was the first country to report a generalised epidemic and to show a decline
in the prevalence of HIV among the general population. Sexual behaviour data
including AFS have been collected in several Demographic and Health Surveys (DHS)
over the past 15 years,<xref ref-type="bibr" rid="b11">11</xref>
and have been
collected from two population-based cohorts in south western Uganda. There is a
considerable literature on changes in sexual behaviour and their influence on the
decline in HIV prevalence in Uganda during the 1990s.<xref ref-type="bibr" rid="b12">12</xref>
<xref ref-type="bibr" rid="b13">13</xref>
This highly charged debate has largely
concluded that a multifactorial response—and not one simple behaviour
change—was key to the decline in prevalence.<xref ref-type="bibr" rid="b14">14</xref>
<xref ref-type="bibr" rid="b15">15</xref>
A secondary but crucial point is that data
from the relevant time period are inadequate to settle the debate.<xref ref-type="bibr" rid="b16">16</xref>
<xref ref-type="bibr" rid="b17">17</xref>
</p>
<p>AFS is the only behavioural measure for which historical trends can be reconstructed
using more recently reported recall data. These trends can be difficult to identify
using data from a series of cross-sectional surveys because observed change could be
due to differences in data quality between surveys or to changes in the composition
of the population between the time of AFS and the time of the survey or between
surveys. If these differences are related to AFS—for example, if those
with a younger AFS tend to emigrate or to die prematurely—an artificial
trend may be seen.</p>
<p>We determined the trends in AFS in Uganda by comparing repeated cross-sectional data
from the DHS with data collected from two cohorts in rural Uganda. Changes in
population structure do not affect the cohort data because information is collected
on all individuals during the time they are resident in the area and retained for
later analysis. The data therefore include anyone who subsequently died or moved
away as well as immigrants to the area.</p>
<p>The quality of retrospectively reported data on AFS can be compromised by reporting
bias due to accidental recall errors or through a desire to conform to health
education messages. This can be assessed directly using cohort data and is discussed
elsewhere in this issue. Although considerable variability in response is apparent,
this does not have a directional effect on the results.<xref ref-type="bibr" rid="b18">18</xref>
</p>
<sec sec-type="methods" id="s2"><title>METHODS</title>
<p>Data were used from all the DHS conducted to date in Uganda (1988, 1995, 2000/1 and
2006) and from two longitudinal population-based studies, one in Masaka district and
one in Rakai district. The DHS provides robust national estimates for different time
points, and the methods by which the data are collected are openly available.<xref ref-type="bibr" rid="b11">11</xref>
The cohort data provide detailed information
for two sets of respondents from two districts of Uganda, both of which have been
extensively reported in publications over the past 15 years.<xref ref-type="bibr" rid="b12">12</xref>
<xref ref-type="bibr" rid="b19">19</xref>
<sup>–</sup>
<xref ref-type="bibr" rid="b21">21</xref>
</p>
<sec id="s2a"><title>DHS</title>
<p>Data were obtained for all the DHS conducted in Uganda. In 1988 only women were
interviewed but in subsequent years (1995, 2000/1, 2006) data are available for
men and women. The geographical range of the sample was restricted in 1988
compared with the later surveys. AFS, reported in whole years, is one of the
first questions asked in the section on marriage and sexual behaviour and has
been asked in the same way in all surveys. We have restricted our analysis to
people who were born between 1950 and 1991 and had their first sex between 1960
and 2006; 973 respondents who were born before 1950 were excluded. We have used
the unedited data from the DHS and have not corrected AFS for other reported
ages in the DHS (age at first marriage and age at first birth). National rather
than regional data were used because the number of respondents from the region
that contains Masaka and Rakai districts was inadequate for this analysis.</p>
</sec>
<sec id="s2b"><title>Masaka study</title>
<p>The Medical Research Council (MRC) general population cohort has been described
previously.<xref ref-type="bibr" rid="b12">12</xref>
<xref ref-type="bibr" rid="b19">19</xref>
Briefly, the study is located in a
rural subcounty in Masaka district in south-western Uganda where an open cohort
has participated in annual population-based surveys. In 1989 the census included
10 000 people residing in 15 villages, but in 1999/2000 this expanded
to 18 000 residents in 25 villages. Survey staff administer a risk
factor questionnaire and annually collect a blood sample for HIV testing.
Starting in 1997, AFS was asked as the first question on sexual behaviour, in
the same way in all surveys, and reported in whole years. For this paper,
analysis was restricted to participants born between 1950 and 1994.</p>
</sec>
<sec id="s2c"><title>Rakai study</title>
<p>The Rakai Health Sciences Program (RHSP) has, since 1994, conducted annual
surveys using an open-community cohort of consenting persons aged
15–49 years resident in rural communities of Rakai District,
south-western Uganda.<xref ref-type="bibr" rid="b20">20</xref>
<xref ref-type="bibr" rid="b21">21</xref>
Surveys are conducted annually using a
questionnaire that includes modules on both sociodemographic and behavioural
characteristics. The same question on AFS was asked, in completed years, at the
enrolment visit of a participant during study rounds 4 (1997–8) and
6–10 (1999–2004). This analysis was restricted to
participants born between 1950 and 1989 and resident in 43 communities that have
been followed since 1994.</p>
</sec>
<sec id="s2d"><title>Statistical methods</title>
<p>For the two cohort studies, responses that were older than the age of the
respondent at the time of the survey were excluded from the analysis. For each
participant the most likely AFS was calculated as the age reported in
50% or more of the survey responses, or the mean age if no age was
reported in 50% of the surveys. Stata Version 10 (Stata Corp, College
Station, Texas, USA) was used for all analyses.</p>
<p>For all three studies we defined birth cohorts based on reported age in the DHS
and reported date of birth in the cohort studies. Ten-year birth cohorts, using
1950–9 as the baseline cohort, were used for the analysis. Later
analysis using 5-year birth cohorts was restricted to those born after 1 January
1970, whose first sex occurred when the prevalence of HIV was already high. The
cohort born in 1970–4 was used as the baseline group for
comparison.</p>
<p>For all data we smoothed the distribution by adding a random fraction of a year
to each person’s reported AFS to account for the time between their
birthday and the date of first sex. With this approach it is possible to
estimate summary measures for the population in increments of <1 year.
Ten replications of each of the datasets were created using different
simulations of the random fraction and the Stata command
<italic>micombine</italic>
was used for the formal comparisons.<xref ref-type="bibr" rid="b22">22</xref>
</p>
<p>Age-to-event analysis (ie, survival before sexual debut) was used to summarise
the median age and interquartile range (IQR) of AFS. Curves plotting the
cumulative proportion who have had sex at any given age are used to display the
pattern of sexual debut.<xref ref-type="bibr" rid="b23">23</xref>
Cox regression
models (accounting for the survey design for DHS data; Stata Version 10) were
used to look for changes in the median AFS by birth cohort. For the DHS data,
these analyses were repeated for each survey and by selected background
characteristics.</p>
</sec>
</sec>
<sec sec-type="" id="s3"><title>RESULTS</title>
<p>The number of male and female respondents in each of the DHS and from the Masaka and
Rakai study by year of birth is shown in <xref ref-type="table" rid="U9G-85-S1-0012-t01"></xref>
<xref ref-type="table" rid="U9G-85-S1-0012-t02">tables
1 and 2</xref>
. These tables also show the median AFS by birth cohort for each
data source. From the DHS, a consistent increase in the median AFS was seen for
women and a similar trend was apparent for young men. However, the composition of
the DHS changes over time as each survey captures a different set of birth
cohorts.</p>
<table-wrap id="U9G-85-S1-0012-t01" position="float"><label>Table 1</label>
<caption><title>Number of male respondents by survey and year of birth, and median age at
first sex (AFS) for each survey (for all DHS and for the Masaka and Rakai
studies)</title>
</caption>
<table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
</colgroup>
<thead><tr><td rowspan="2" align="left" colspan="1">Year of birth</td>
<td colspan="5" align="left" rowspan="1">DHS</td>
<td colspan="2" align="left" rowspan="1">Masakacohort</td>
<td colspan="2" align="left" rowspan="1">Rakaicohort</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1995</td>
<td align="left" rowspan="1" colspan="1">2001</td>
<td align="left" rowspan="1" colspan="1">2006</td>
<td align="left" rowspan="1" colspan="1">Total</td>
<td align="left" rowspan="1" colspan="1">Median AFS†</td>
<td align="left" rowspan="1" colspan="1">N</td>
<td align="left" rowspan="1" colspan="1">Median AFS</td>
<td align="left" rowspan="1" colspan="1">N</td>
<td align="left" rowspan="1" colspan="1">Median AFS</td>
</tr>
</thead>
<tbody><tr><td align="left" rowspan="1" colspan="1">1950–9</td>
<td align="char" rowspan="1" colspan="1">384</td>
<td align="char" rowspan="1" colspan="1">260</td>
<td align="char" rowspan="1" colspan="1">205</td>
<td align="char" rowspan="1" colspan="1">849</td>
<td align="char" rowspan="1" colspan="1">18.1</td>
<td align="char" rowspan="1" colspan="1">492</td>
<td align="char" rowspan="1" colspan="1">18.5</td>
<td align="char" rowspan="1" colspan="1">852</td>
<td align="char" rowspan="1" colspan="1">18.1</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1960–9</td>
<td align="char" rowspan="1" colspan="1">636</td>
<td align="char" rowspan="1" colspan="1">494</td>
<td align="char" rowspan="1" colspan="1">502</td>
<td align="char" rowspan="1" colspan="1">1632</td>
<td align="char" rowspan="1" colspan="1">18.2</td>
<td align="char" rowspan="1" colspan="1">843</td>
<td align="char" rowspan="1" colspan="1">18.2</td>
<td align="char" rowspan="1" colspan="1">2060</td>
<td align="char" rowspan="1" colspan="1">17.9</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1970–9</td>
<td align="char" rowspan="1" colspan="1">767</td>
<td align="char" rowspan="1" colspan="1">631</td>
<td align="char" rowspan="1" colspan="1">690</td>
<td align="char" rowspan="1" colspan="1">2088</td>
<td align="char" rowspan="1" colspan="1">18.0</td>
<td align="char" rowspan="1" colspan="1">1389</td>
<td align="char" rowspan="1" colspan="1">18.0</td>
<td align="char" rowspan="1" colspan="1">4060</td>
<td align="char" rowspan="1" colspan="1">17.8</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1980–9</td>
<td align="char" rowspan="1" colspan="1">25</td>
<td align="char" rowspan="1" colspan="1">524</td>
<td align="char" rowspan="1" colspan="1">874</td>
<td align="char" rowspan="1" colspan="1">1423</td>
<td align="char" rowspan="1" colspan="1">17.9</td>
<td align="char" rowspan="1" colspan="1">2781</td>
<td align="char" rowspan="1" colspan="1">18.5</td>
<td align="char" rowspan="1" colspan="1">2821</td>
<td align="char" rowspan="1" colspan="1">17.1</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1990–4</td>
<td align="char" rowspan="1" colspan="1">0</td>
<td align="char" rowspan="1" colspan="1">0</td>
<td align="left" rowspan="1" colspan="1">232*</td>
<td align="left" rowspan="1" colspan="1">232*</td>
<td align="char" rowspan="1" colspan="1">18.1*</td>
<td align="char" rowspan="1" colspan="1">933</td>
<td align="char" rowspan="1" colspan="1">17.1</td>
<td align="char" rowspan="1" colspan="1">0</td>
<td align="char" rowspan="1" colspan="1">–</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Total</td>
<td align="char" rowspan="1" colspan="1">1812</td>
<td align="char" rowspan="1" colspan="1">1909</td>
<td align="char" rowspan="1" colspan="1">2503</td>
<td align="char" rowspan="1" colspan="1">6224</td>
<td align="char" rowspan="1" colspan="1">18.0</td>
<td align="char" rowspan="1" colspan="1">6438</td>
<td align="char" rowspan="1" colspan="1">18.2</td>
<td align="char" rowspan="1" colspan="1">9793</td>
<td align="char" rowspan="1" colspan="1">17.7</td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="nt101"><p>DHS, Demographic and Health Survey.</p>
</fn>
<fn id="nt102"><p>*1990–1 only.</p>
</fn>
<fn id="nt103"><p>†Based on data from all surveys.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="U9G-85-S1-0012-t02" position="float"><label>Table 2</label>
<caption><title>Number of female respondents by survey and year of birth, and median age
at first sex (AFS) for each survey (for all DHS and for the Masaka and Rakai
studies)</title>
</caption>
<table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
</colgroup>
<thead><tr><td rowspan="2" align="left" colspan="1">Year of birth</td>
<td colspan="6" align="left" rowspan="1">DHS</td>
<td colspan="2" align="left" rowspan="1">Masakacohort</td>
<td colspan="2" align="left" rowspan="1">Rakaicohort</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1988</td>
<td align="left" rowspan="1" colspan="1">1995</td>
<td align="left" rowspan="1" colspan="1">2001</td>
<td align="left" rowspan="1" colspan="1">2006</td>
<td align="left" rowspan="1" colspan="1">Total</td>
<td align="left" rowspan="1" colspan="1">Median AFS†</td>
<td align="left" rowspan="1" colspan="1">N</td>
<td align="left" rowspan="1" colspan="1">Median AFS</td>
<td align="left" rowspan="1" colspan="1">N</td>
<td align="left" rowspan="1" colspan="1">Median AFS</td>
</tr>
</thead>
<tbody><tr><td align="left" rowspan="1" colspan="1">1950–9</td>
<td align="char" rowspan="1" colspan="1">1158</td>
<td align="char" rowspan="1" colspan="1">1171</td>
<td align="char" rowspan="1" colspan="1">777</td>
<td align="char" rowspan="1" colspan="1">360</td>
<td align="char" rowspan="1" colspan="1">3466</td>
<td align="char" rowspan="1" colspan="1">15.9</td>
<td align="char" rowspan="1" colspan="1">581</td>
<td align="char" rowspan="1" colspan="1">16.6</td>
<td align="char" rowspan="1" colspan="1">1039</td>
<td align="char" rowspan="1" colspan="1">15.9</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1960–9</td>
<td align="char" rowspan="1" colspan="1">1948</td>
<td align="char" rowspan="1" colspan="1">2273</td>
<td align="char" rowspan="1" colspan="1">1604</td>
<td align="char" rowspan="1" colspan="1">1553</td>
<td align="char" rowspan="1" colspan="1">7378</td>
<td align="char" rowspan="1" colspan="1">16.1</td>
<td align="char" rowspan="1" colspan="1">1030</td>
<td align="char" rowspan="1" colspan="1">16.8</td>
<td align="char" rowspan="1" colspan="1">2196</td>
<td align="char" rowspan="1" colspan="1">16.0</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1970–9</td>
<td align="char" rowspan="1" colspan="1">947</td>
<td align="char" rowspan="1" colspan="1">3199</td>
<td align="char" rowspan="1" colspan="1">2805</td>
<td align="char" rowspan="1" colspan="1">2497</td>
<td align="char" rowspan="1" colspan="1">9448</td>
<td align="char" rowspan="1" colspan="1">16.4</td>
<td align="char" rowspan="1" colspan="1">1768</td>
<td align="char" rowspan="1" colspan="1">17.0</td>
<td align="char" rowspan="1" colspan="1">5606</td>
<td align="char" rowspan="1" colspan="1">16.6</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1980–9</td>
<td align="char" rowspan="1" colspan="1">0</td>
<td align="char" rowspan="1" colspan="1">131</td>
<td align="char" rowspan="1" colspan="1">2060</td>
<td align="char" rowspan="1" colspan="1">3366</td>
<td align="char" rowspan="1" colspan="1">5557</td>
<td align="char" rowspan="1" colspan="1">17.1</td>
<td align="char" rowspan="1" colspan="1">3235</td>
<td align="char" rowspan="1" colspan="1">17.5</td>
<td align="char" rowspan="1" colspan="1">4853</td>
<td align="char" rowspan="1" colspan="1">16.5</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1990–94</td>
<td align="char" rowspan="1" colspan="1">0</td>
<td align="char" rowspan="1" colspan="1">0</td>
<td align="char" rowspan="1" colspan="1">0</td>
<td align="left" rowspan="1" colspan="1">755*</td>
<td align="left" rowspan="1" colspan="1">755*</td>
<td align="char" rowspan="1" colspan="1">–</td>
<td align="char" rowspan="1" colspan="1">829</td>
<td align="char" rowspan="1" colspan="1">16.9</td>
<td align="char" rowspan="1" colspan="1">0</td>
<td align="char" rowspan="1" colspan="1">–</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Total</td>
<td align="char" rowspan="1" colspan="1">4053</td>
<td align="char" rowspan="1" colspan="1">6774</td>
<td align="char" rowspan="1" colspan="1">7246</td>
<td align="char" rowspan="1" colspan="1">8531</td>
<td align="char" rowspan="1" colspan="1">26604</td>
<td align="char" rowspan="1" colspan="1">16.4</td>
<td align="char" rowspan="1" colspan="1">7443</td>
<td align="char" rowspan="1" colspan="1">17.1</td>
<td align="char" rowspan="1" colspan="1">13694</td>
<td align="char" rowspan="1" colspan="1">16.4</td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="nt104"><p>DHS, Demographic and Health Survey.</p>
</fn>
<fn id="nt105"><p>*1990–1 only.</p>
</fn>
<fn id="nt106"><p>†Based on data from all surveys.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>Survival curves by 10-year birth cohorts are shown in <xref ref-type="fig" rid="U9G-85-S1-0012-f01">fig 1</xref>
. <xref ref-type="fig" rid="U9G-85-S1-0012-f01">Figure 1A</xref>
combines the data from all four of the
DHS, and the curves suggest that there has been a change towards a later AFS for
women. The pattern of the change appears to be different for men and women: the
female cohorts born in the 1980s appear to be delaying first sex from the outset,
whereas there has been little change in the proportion of men who have had sex at
the younger ages. The survival curves for women in the Masaka study (<xref ref-type="fig" rid="U9G-85-S1-0012-f01">fig 1B</xref>
) and the Rakai study
(<xref ref-type="fig" rid="U9G-85-S1-0012-f01">fig 1C</xref>
) show a similar
pattern to those from the DHS, with the female cohorts of the 1970s, 1980s and 1990s
showing a delay in AFS. In Masaka women the AFS is slightly higher than that
reported in the DHS study and in the Rakai cohort (<xref ref-type="table" rid="U9G-85-S1-0012-t02">table 2</xref>
and <xref ref-type="fig" rid="U9G-85-S1-0012-f01">fig 1</xref>
), and the delay in AFS among the 1980s
birth cohort appears to be smaller in the Rakai cohort than in the DHS data and the
Masaka cohort. For men, there seems to be some delay in AFS in the 1970s and 1980s
birth cohorts in Masaka, but an earlier AFS in the 1980s birth cohort in Rakai
(<xref ref-type="fig" rid="U9G-85-S1-0012-f01">fig 1</xref>
).</p>
<fig id="U9G-85-S1-0012-f01" position="float"><label>Figure 1</label>
<caption><p>Survival curves (cumulative proportion that has had sex by age) for men and
women by 10-year birth cohorts. (A) Pooled Demographic and Health Survey
data; (B) Masaka study; (C) Rakai study.</p>
</caption>
<graphic xlink:href="U9G-85-S1-0012-f01"></graphic>
</fig>
<p><xref ref-type="table" rid="U9G-85-S1-0012-t03">Table 3</xref>
translates these
survival curves into relative hazards for the 10-year birth cohorts taking a
baseline of those born in 1950–9. There is strong evidence from the DHS
and the Masaka study that women in the 1980s and 1990s cohorts are starting sex
later, with significantly lower relative hazards for those born in the 1970s, 1980s
and 1990s compared with the baseline cohort of the 1950s. For the women in Rakai a
significantly lower hazard is seen for the cohort born in the 1970s, but there was
no significant difference in hazard for starting sex between those born in the 1980s
and those born in the 1950s. For men, both the DHS and the Masaka study showed a
trend towards delayed AFS in the later birth cohorts, but the only significant
effects were seen in Masaka with a higher relative hazard in those born in the 1970s
and a lower hazard in those born in the 1990s. Conversely, the trend in Rakai was
towards an earlier AFS, with a significantly higher relative hazard in the cohort
born in the 1980s compared with those born in the 1950s.</p>
<table-wrap id="U9G-85-S1-0012-t03" position="float"><label>Table 3</label>
<caption><title>Crude hazard ratios (HRs) from Cox regression models showing the effect
of 10-year birth cohorts on survival time to first sex (data from pooled
DHS, Masaka study and Rakai study)</title>
</caption>
<table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
</colgroup>
<thead><tr><td rowspan="2" align="left" colspan="1">Year of birth</td>
<td colspan="2" align="left" rowspan="1">DHS</td>
<td colspan="2" align="left" rowspan="1">Masaka</td>
<td colspan="2" align="left" rowspan="1">Rakai</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Crude HR</td>
<td align="left" rowspan="1" colspan="1">p Value</td>
<td align="left" rowspan="1" colspan="1">Crude HR</td>
<td align="left" rowspan="1" colspan="1">p Value</td>
<td align="left" rowspan="1" colspan="1">Crude HR</td>
<td align="left" rowspan="1" colspan="1">p Value</td>
</tr>
</thead>
<tbody><tr><td align="left" rowspan="1" colspan="1"><italic>Men</italic>
</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1950–9</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1960–9</td>
<td align="left" rowspan="1" colspan="1">1.08 (0.98 to 1.19)</td>
<td align="char" rowspan="1" colspan="1">0.130</td>
<td align="left" rowspan="1" colspan="1">1.19 (1.06 to 1.33)</td>
<td align="char" rowspan="1" colspan="1">0.004</td>
<td align="left" rowspan="1" colspan="1">1.03 (0.95 to 1.11)</td>
<td align="char" rowspan="1" colspan="1">0.5</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1970–9</td>
<td align="left" rowspan="1" colspan="1">1.08 (0.99 to 1.18)</td>
<td align="char" rowspan="1" colspan="1">0.096</td>
<td align="left" rowspan="1" colspan="1">1.29 (1.15 to 1.44)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">1.05 (0.98 to 1.13)</td>
<td align="char" rowspan="1" colspan="1">0.16</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1980–9</td>
<td align="left" rowspan="1" colspan="1">0.93 (0.83 to 1.05)</td>
<td align="char" rowspan="1" colspan="1">0.253</td>
<td align="left" rowspan="1" colspan="1">0.98 (0.87 to 1.11)</td>
<td align="char" rowspan="1" colspan="1">0.79</td>
<td align="left" rowspan="1" colspan="1">1.61 (1.49 to 1.74)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1990–4</td>
<td align="left" rowspan="1" colspan="1">0.86 (0.61 to 1.21)</td>
<td align="char" rowspan="1" colspan="1">0.383</td>
<td align="left" rowspan="1" colspan="1">0.32 (0.19 to 0.64)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">–</td>
<td align="char" rowspan="1" colspan="1">–</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Total</td>
<td align="left" rowspan="1" colspan="1">6113</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">5655</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">11211</td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"><italic>Women</italic>
</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1950–9</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1960–9</td>
<td align="left" rowspan="1" colspan="1">0.94 (0.9 to 0.99)</td>
<td align="char" rowspan="1" colspan="1">0.017</td>
<td align="left" rowspan="1" colspan="1">0.92 (0.83 to 1.02)</td>
<td align="char" rowspan="1" colspan="1">0.11</td>
<td align="left" rowspan="1" colspan="1">0.96 (0.89 to 1.03)</td>
<td align="char" rowspan="1" colspan="1">0.3</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1970–9</td>
<td align="left" rowspan="1" colspan="1">0.87 (0.83 to 0.92)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">0.83 (0.75 to 0.91)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">0.81 (0.76 to 0.87)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1980–9</td>
<td align="left" rowspan="1" colspan="1">0.67 (0.63 to 0.71)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">0.62 (0.57 to 0.69)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">1.03 (0.96 to 1.11)</td>
<td align="char" rowspan="1" colspan="1">0.36</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1990–4</td>
<td align="left" rowspan="1" colspan="1">0.37 (0.3 to 0.44)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">0.23 (0.15 to 0.35)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">–</td>
<td align="char" rowspan="1" colspan="1">–</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Total</td>
<td align="left" rowspan="1" colspan="1">26531</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">6880</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">14808</td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="nt107"><p>DHS, Demographic and Health Survey.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>In restricting the analysis to those born after 1 January 1970, the survival curves
for 5-year birth cohorts are shown in <xref ref-type="fig" rid="U9G-85-S1-0012-f02">fig 2</xref>
and the relative hazards in <xref ref-type="table" rid="U9G-85-S1-0012-t04">table 4</xref>
. In the DHS and Masaka studies, men and
women in the later cohorts (those born in 1980–4 and 1985–9)
had delayed AFS (<xref ref-type="fig" rid="U9G-85-S1-0012-f02">fig 2</xref>
). The
Rakai data show the opposite, with the later cohorts having earlier AFS. This
pattern is clearly seen in the hazard ratios for AFS in <xref ref-type="table" rid="U9G-85-S1-0012-t04">table 4</xref>
, which shows increased hazard in the
later cohorts in Rakai but reduced hazards in the DHS and Masaka studies.</p>
<fig id="U9G-85-S1-0012-f02" position="float"><label>Figure 2</label>
<caption><p>Survival curves (cumulative proportion who have had sex by age) for men and
women born since 1970 by 5-year birth cohorts. (A) Pooled Demographic and
Health Survey data; (B) Masaka study; (C) Rakai study.</p>
</caption>
<graphic xlink:href="U9G-85-S1-0012-f02"></graphic>
</fig>
<table-wrap id="U9G-85-S1-0012-t04" position="float"><label>Table 4</label>
<caption><title>Crude hazard ratios (HRs) from Cox regression models showing the effect
of 5-year birth cohorts on survival time to first sex (data from pooled DHS,
Masaka study and Rakai study)</title>
</caption>
<table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
</colgroup>
<thead><tr><td rowspan="2" align="left" colspan="1">Year of birth</td>
<td colspan="2" align="left" rowspan="1">DHS</td>
<td colspan="2" align="left" rowspan="1">Masaka</td>
<td colspan="2" align="left" rowspan="1">Rakai</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Crude HR</td>
<td align="left" rowspan="1" colspan="1">p Value</td>
<td align="left" rowspan="1" colspan="1">Crude HR</td>
<td align="left" rowspan="1" colspan="1">p Value</td>
<td align="left" rowspan="1" colspan="1">Crude HR</td>
<td align="left" rowspan="1" colspan="1">p Value</td>
</tr>
</thead>
<tbody><tr><td align="left" rowspan="1" colspan="1"><italic>Men</italic>
</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1970–4</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1975–9</td>
<td align="left" rowspan="1" colspan="1">0.99 (0.89 to 1.1)</td>
<td align="char" rowspan="1" colspan="1">0.81</td>
<td align="left" rowspan="1" colspan="1">1.02 (0.91 to 1.15)</td>
<td align="char" rowspan="1" colspan="1">0.7</td>
<td align="left" rowspan="1" colspan="1">1.10 (1.03 to 1.17)</td>
<td align="char" rowspan="1" colspan="1">0.002</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1980–4</td>
<td align="left" rowspan="1" colspan="1">0.88 (0.77 to 1.0)</td>
<td align="char" rowspan="1" colspan="1">0.059</td>
<td align="left" rowspan="1" colspan="1">0.94 (0.83 to 1.06)</td>
<td align="char" rowspan="1" colspan="1">0.29</td>
<td align="left" rowspan="1" colspan="1">1.59 (1.49 to 1.71)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1985–9</td>
<td align="left" rowspan="1" colspan="1">0.82 (0.70 to 0.96)</td>
<td align="char" rowspan="1" colspan="1">0.011</td>
<td align="left" rowspan="1" colspan="1">0.51 (0.44 to 0.59)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">1.58 (1.42 to 1.76)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1990–4</td>
<td align="left" rowspan="1" colspan="1">0.8 (0.57 to 1.12)</td>
<td align="char" rowspan="1" colspan="1">0.187</td>
<td align="left" rowspan="1" colspan="1">0.21 (0.12 to 0.34)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">–</td>
<td align="char" rowspan="1" colspan="1">–</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Total</td>
<td align="left" rowspan="1" colspan="1">3662</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">4398</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">8013</td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"><italic>Women</italic>
</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1970–4</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1975–9</td>
<td align="left" rowspan="1" colspan="1">0.97 (0.92 to 1.03)</td>
<td align="char" rowspan="1" colspan="1">0.301</td>
<td align="left" rowspan="1" colspan="1">0.93 (0.84 to 1.02)</td>
<td align="char" rowspan="1" colspan="1">0.13</td>
<td align="left" rowspan="1" colspan="1">0.94 (0.89 to 0.99)</td>
<td align="char" rowspan="1" colspan="1">0.016</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1980–4</td>
<td align="left" rowspan="1" colspan="1">0.82 (0.77 to 0.86)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">0.84 (0.76 to 0.93)</td>
<td align="char" rowspan="1" colspan="1">0.001</td>
<td align="left" rowspan="1" colspan="1">1.20 (1.13 to 1.26)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1985–9</td>
<td align="left" rowspan="1" colspan="1">0.67 (0.62 to 0.73)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">0.54 (0.48 to 0.61)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">1.37 (1.27 to 1.49)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1990–4</td>
<td align="left" rowspan="1" colspan="1">0.44 (0.37 to 0.54)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">0.27 (0.18 to 0.41)</td>
<td align="char" rowspan="1" colspan="1"><0.001</td>
<td align="left" rowspan="1" colspan="1">–</td>
<td align="char" rowspan="1" colspan="1">–</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Total</td>
<td align="left" rowspan="1" colspan="1">15734</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">5328</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">11707</td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="nt108"><p>Restricted to those born on or after 1 January 1970.</p>
</fn>
<fn id="nt109"><p>DHS, Demographic and Health Survey.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>Using data from the DHS, restricted to those born after 1 January 1970, comparisons
can be made between those with different characteristics (<xref ref-type="table" rid="U9G-85-S1-0012-t05">table 5</xref>
). AFS was delayed in later female birth
cohorts, with a similar highly significant pattern in all regions (<xref ref-type="table" rid="U9G-85-S1-0012-t05">table 5</xref>
). The delay in AFS was
not seen in women with secondary education and was much smaller in women in the
richest quintile. For men a smaller overall effect was seen (<xref ref-type="table" rid="U9G-85-S1-0012-t04">table 4</xref>
). The delay in AFS in men born in the
1980s was seen as significant in urban areas and in those with no education (<xref ref-type="table" rid="U9G-85-S1-0012-t05">table 5</xref>
).</p>
<table-wrap id="U9G-85-S1-0012-t05" position="float"><label>Table 5</label>
<caption><title>Hazard ratios (HRs) from Cox regression models showing the effect of
5-year birth cohorts on survival time to first sex (for pooled DHS data),
stratified for area of residence, region, education and wealth</title>
</caption>
<table frame="hsides" rules="groups"><colgroup span="1"><col align="left" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
<col align="center" span="1"></col>
</colgroup>
<thead><tr><td rowspan="2" align="left" colspan="1"></td>
<td rowspan="2" align="left" colspan="1">Median AFS 1970–4 cohort</td>
<td colspan="5" align="left" rowspan="1">HRs by birth cohort</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">1970–4</td>
<td align="left" rowspan="1" colspan="1">1975–9</td>
<td align="left" rowspan="1" colspan="1">1980–4</td>
<td align="left" rowspan="1" colspan="1">1985–9</td>
<td align="left" rowspan="1" colspan="1">1990–1</td>
</tr>
</thead>
<tbody><tr><td align="left" rowspan="1" colspan="1"><italic>Men</italic>
</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">All subjects (N)</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">1002</td>
<td align="left" rowspan="1" colspan="1">1041</td>
<td align="left" rowspan="1" colspan="1">831</td>
<td align="left" rowspan="1" colspan="1">558</td>
<td align="left" rowspan="1" colspan="1">230</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">All subjects (HR)</td>
<td align="left" rowspan="1" colspan="1">17.7</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.99</td>
<td align="left" rowspan="1" colspan="1">0.88</td>
<td align="left" rowspan="1" colspan="1"><bold>0.82*</bold>
</td>
<td align="left" rowspan="1" colspan="1">0.8</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Area (urban/rural)</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Urban</td>
<td align="left" rowspan="1" colspan="1">17.1</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"><bold>0.78*</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.76*</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.69*</bold>
</td>
<td align="left" rowspan="1" colspan="1">0.48</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Rural</td>
<td align="left" rowspan="1" colspan="1">17.9</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">1.04</td>
<td align="left" rowspan="1" colspan="1">0.91</td>
<td align="left" rowspan="1" colspan="1">0.85</td>
<td align="left" rowspan="1" colspan="1">0.88</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Region</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Central†</td>
<td align="left" rowspan="1" colspan="1">17.5</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.95</td>
<td align="left" rowspan="1" colspan="1">0.99</td>
<td align="left" rowspan="1" colspan="1">0.96</td>
<td align="left" rowspan="1" colspan="1">0.64</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Eastern</td>
<td align="left" rowspan="1" colspan="1">17.0</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.97</td>
<td align="left" rowspan="1" colspan="1">0.82</td>
<td align="left" rowspan="1" colspan="1"><bold>0.63*</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.43*</bold>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Northern</td>
<td align="left" rowspan="1" colspan="1">18.2</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">1.22</td>
<td align="left" rowspan="1" colspan="1">0.95</td>
<td align="left" rowspan="1" colspan="1">1.14</td>
<td align="left" rowspan="1" colspan="1"><bold>1.62*</bold>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Western</td>
<td align="left" rowspan="1" colspan="1">18.0</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.90</td>
<td align="left" rowspan="1" colspan="1"><bold>0.72*</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.67*</bold>
</td>
<td align="left" rowspan="1" colspan="1">0.8</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Education</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> None</td>
<td align="left" rowspan="1" colspan="1">17.6</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.87</td>
<td align="left" rowspan="1" colspan="1">0.88</td>
<td align="left" rowspan="1" colspan="1">0.39</td>
<td align="left" rowspan="1" colspan="1">N/A</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Primary</td>
<td align="left" rowspan="1" colspan="1">17.6</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">1.02</td>
<td align="left" rowspan="1" colspan="1">0.85</td>
<td align="left" rowspan="1" colspan="1">0.85</td>
<td align="left" rowspan="1" colspan="1">0.68</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Secondary and
above</td>
<td align="left" rowspan="1" colspan="1">18.1</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.97</td>
<td align="left" rowspan="1" colspan="1">0.97</td>
<td align="left" rowspan="1" colspan="1">0.84</td>
<td align="left" rowspan="1" colspan="1">1.71</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Wealth ranking</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Poorest</td>
<td align="left" rowspan="1" colspan="1">17.3</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">1.0</td>
<td align="left" rowspan="1" colspan="1">0.86</td>
<td align="left" rowspan="1" colspan="1">0.73</td>
<td align="left" rowspan="1" colspan="1">1.3</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Poor</td>
<td align="left" rowspan="1" colspan="1">18.4</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"><bold>1.36*</bold>
</td>
<td align="left" rowspan="1" colspan="1">1.19</td>
<td align="left" rowspan="1" colspan="1">0.96</td>
<td align="left" rowspan="1" colspan="1">0.75</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Middle</td>
<td align="left" rowspan="1" colspan="1">17.7</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.82</td>
<td align="left" rowspan="1" colspan="1">0.93</td>
<td align="left" rowspan="1" colspan="1">0.84</td>
<td align="left" rowspan="1" colspan="1">0.71</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Rich</td>
<td align="left" rowspan="1" colspan="1">15.7</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.82</td>
<td align="left" rowspan="1" colspan="1">0.79</td>
<td align="left" rowspan="1" colspan="1">0.73</td>
<td align="left" rowspan="1" colspan="1">0.93</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Richest</td>
<td align="left" rowspan="1" colspan="1">16.2</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1"><bold>0.93</bold>
</td>
<td align="left" rowspan="1" colspan="1">0.87</td>
<td align="left" rowspan="1" colspan="1">1.0</td>
<td align="left" rowspan="1" colspan="1">0.75</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Year of survey</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> 1995</td>
<td align="left" rowspan="1" colspan="1">17.5</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.92</td>
<td align="left" rowspan="1" colspan="1">0.51</td>
<td align="left" rowspan="1" colspan="1">–</td>
<td align="left" rowspan="1" colspan="1">–</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> 2001</td>
<td align="left" rowspan="1" colspan="1">18.1</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">1.02</td>
<td align="left" rowspan="1" colspan="1">0.95</td>
<td align="left" rowspan="1" colspan="1">0.6</td>
<td align="left" rowspan="1" colspan="1">–</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> 2006</td>
<td align="left" rowspan="1" colspan="1">17.6</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.97</td>
<td align="left" rowspan="1" colspan="1">0.9</td>
<td align="left" rowspan="1" colspan="1"><bold>0.83*</bold>
</td>
<td align="left" rowspan="1" colspan="1">0.85</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"><italic>Women</italic>
</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">All subjects (N)</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1">4893</td>
<td align="left" rowspan="1" colspan="1">4532</td>
<td align="left" rowspan="1" colspan="1">3454</td>
<td align="left" rowspan="1" colspan="1">2101</td>
<td align="left" rowspan="1" colspan="1">754</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">All subjects (HR)</td>
<td align="char" rowspan="1" colspan="1">16.4</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.97</td>
<td align="left" rowspan="1" colspan="1"><bold>0.82***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.67***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.44***</bold>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Area (urban/rural)</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Urban</td>
<td align="char" rowspan="1" colspan="1">16.6</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.94</td>
<td align="left" rowspan="1" colspan="1"><bold>0.79***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.67***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.61**</bold>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Rural</td>
<td align="char" rowspan="1" colspan="1">16.3</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.99</td>
<td align="left" rowspan="1" colspan="1"><bold>0.84***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.69***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.42***</bold>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Region</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Central†</td>
<td align="char" rowspan="1" colspan="1">16.1</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.97</td>
<td align="left" rowspan="1" colspan="1"><bold>0.81***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.61***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.44***</bold>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Eastern</td>
<td align="char" rowspan="1" colspan="1">15.8</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.96</td>
<td align="left" rowspan="1" colspan="1"><bold>0.83***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.68***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.47***</bold>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Northern</td>
<td align="char" rowspan="1" colspan="1">16.5</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.97</td>
<td align="left" rowspan="1" colspan="1"><bold>0.82**</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.71***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.34***</bold>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Western</td>
<td align="char" rowspan="1" colspan="1">17.0</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.96</td>
<td align="left" rowspan="1" colspan="1"><bold>0.82**</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.71***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.49**</bold>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Education</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> None</td>
<td align="char" rowspan="1" colspan="1">15.9</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.99</td>
<td align="left" rowspan="1" colspan="1">0.98</td>
<td align="left" rowspan="1" colspan="1">0.77</td>
<td align="left" rowspan="1" colspan="1">0.41</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Primary</td>
<td align="char" rowspan="1" colspan="1">16.2</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">1.04</td>
<td align="left" rowspan="1" colspan="1"><bold>0.81***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.7***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.42***</bold>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Secondary and
above</td>
<td align="char" rowspan="1" colspan="1">17.9</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.92</td>
<td align="left" rowspan="1" colspan="1">0.94</td>
<td align="left" rowspan="1" colspan="1">0.87</td>
<td align="left" rowspan="1" colspan="1">0.91</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Wealth ranking</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Poorest</td>
<td align="char" rowspan="1" colspan="1">16.0</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">1.05</td>
<td align="left" rowspan="1" colspan="1">0.94</td>
<td align="left" rowspan="1" colspan="1">0.82</td>
<td align="left" rowspan="1" colspan="1">0.35</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Poor</td>
<td align="char" rowspan="1" colspan="1">16.3</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.99</td>
<td align="left" rowspan="1" colspan="1">0.91</td>
<td align="left" rowspan="1" colspan="1"><bold>0.78**</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.36***</bold>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Middle</td>
<td align="char" rowspan="1" colspan="1">15.1</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">1.09</td>
<td align="left" rowspan="1" colspan="1"><bold>0.83**</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.6***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.45**</bold>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Rich</td>
<td align="char" rowspan="1" colspan="1">15.0</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.9</td>
<td align="left" rowspan="1" colspan="1"><bold>0.7***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.57***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.43***</bold>
</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> Richest</td>
<td align="char" rowspan="1" colspan="1">17.1</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.88</td>
<td align="left" rowspan="1" colspan="1"><bold>0.76**</bold>
</td>
<td align="left" rowspan="1" colspan="1">0.75</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1">Year of survey</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> 1995</td>
<td align="char" rowspan="1" colspan="1">16.3</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.98</td>
<td align="left" rowspan="1" colspan="1">0.67</td>
<td align="left" rowspan="1" colspan="1"></td>
<td align="left" rowspan="1" colspan="1"></td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> 2001</td>
<td align="char" rowspan="1" colspan="1">16.6</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">1.04</td>
<td align="left" rowspan="1" colspan="1"><bold>0.89*</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.56***</bold>
</td>
<td align="left" rowspan="1" colspan="1">–</td>
</tr>
<tr><td align="left" rowspan="1" colspan="1"> 2006</td>
<td align="char" rowspan="1" colspan="1">16.2</td>
<td align="left" rowspan="1" colspan="1">1</td>
<td align="left" rowspan="1" colspan="1">0.93</td>
<td align="left" rowspan="1" colspan="1"><bold>0.8***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.65***</bold>
</td>
<td align="left" rowspan="1" colspan="1"><bold>0.42***</bold>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="nt110"><p>Restricted to those born on or after 1 January 1970.</p>
</fn>
<fn id="nt111"><p>All birth cohorts compared with those born in 1970–4.</p>
</fn>
<fn id="nt112"><p>*p<0.05; **p<0.01;
***p<0.001.</p>
</fn>
<fn id="nt113"><p>†Central region contains Masaka and Rakai districts.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec sec-type="" id="s4"><title>DISCUSSION</title>
<p>Results from the DHS and from the Masaka study show a clear trend towards a delay in
starting sex among women in Uganda, with those born in the 1980s reporting AFS about
1 year later than those born in the 1950s. A smaller delay was seen among women in
Rakai who were born in the 1970s and the 1980s compared with those born in the
1950s. The change in AFS in men is less clear; in the DHS data no significant
difference was seen between any of the male birth cohorts, and little evidence of a
delay in AFS in either Masaka or Rakai. In the latest birth cohorts (born in the
1990s), the data from both DHS and Masaka indicate the possibility that AFS has been
delayed even further in both women and men. However, this was based on small numbers
and needs further follow-up to confirm the findings. These findings agree with other
analyses of changes in sexual behaviour in young people in sub-Saharan Africa<xref ref-type="bibr" rid="b6">6</xref>
<xref ref-type="bibr" rid="b7">7</xref>
and in Uganda.<xref ref-type="bibr" rid="b13">13</xref>
<xref ref-type="bibr" rid="b14">14</xref>
</p>
<p>By looking at the whole of the survival function rather than just the median AFS, it
is clear that the pattern of change has been different for men and women and that
the youngest women in the more recent cohorts are delaying sex but their male
counterparts are not. In all graphs the women have sexual debut over a shorter
period of time than the men, with many birth cohorts showing that some men are still
virgin at the age of 25 years. This may show the choice that men have about sexual
debut which may be denied to women, either through social pressure or through
coercive sex.</p>
<p>The DHS findings show that the changes in the last 20 years have been greatest in
those in the middle income quintiles and those with lower education (primary school
or lower). This may be partly because more wealthy/highly educated young women have
always been able to delay sexual debut, and it is only recently that the less
wealthy and less educated have been able to access the same choices. The median AFS
for women born in the 1970s who had secondary education and were in the richest
quintile was 18.2 years compared with 16.3 years for all other women.</p>
<p>The timing of the observed changes in AFS relative to the decline in the prevalence
of HIV in the early to mid 1990s (see fig S1 in the online supplement<xref ref-type="bibr" rid="b24">24</xref>
<sup>–</sup>
<xref ref-type="bibr" rid="b30">30</xref>
) suggest that these changes have been a response to the
danger of HIV infection, not a cause. To illustrate this, the survival functions can
be plotted over calendar time. Based on DHS data, in 1980, 22% of
14–16-year-old women had had sex; in 1990 this had declined slightly to
20%, but had halved by 2000.</p>
<p>Changes in AFS may have helped to further reduce the incidence but cannot have been a
cause of the initial decline. Young women need the knowledge and ability to delay
first sex. Regardless of the contribution to HIV prevention, if women in Uganda are
increasingly able to delay first sex, this would be a major achievement for the
health messages that have been used over the last 20 years.</p>
<p>The changes in reported AFS in the Rakai study are different from those seen in the
DHS and the Masaka study. There is some evidence that delaying AFS started earlier
in Rakai, with women born in the 1970s who started sex in the late 1980s and early
1990s showing later AFS than those born in the 1950s. This could have occurred
because the prevalence of HIV was higher at an earlier date and the preventive
action by young women was initiated in an earlier birth cohort. However, the effect
in the latest birth cohort of men in Rakai shows earlier AFS and does not fit with
the explanation that changes in the sexual debut of young people are a response to
the HIV infection seen in the community. The result of the changes in the most
recent cohorts is a more similar experience for young men and women, around
one-quarter of whom have started sex by about the age of 15 years in Rakai. Sex
between partners of different ages can be a risk for HIV infection.<xref ref-type="bibr" rid="b31">31</xref>
<xref ref-type="bibr" rid="b32">32</xref>
The availability of more sexually active
young men may reduce age mixing in this community if young women increasingly choose
partners close to their own age. This may be beneficial for HIV prevention, although
any effect may be transient and dependent on other characteristics of the
partnership networks.<xref ref-type="bibr" rid="b33">33</xref>
The difference seen
between the Rakai and Masaka cohorts could be due to the inclusion of trading
centres in the Rakai study which are not seen in Masaka, as these may provide some
employment to younger single women and men, and keep them in the study area. Single
men aged 15–24 years comprised 25% of the Masaka cohort and
29% of the Rakai cohort in 2006. Single women of the same age made up
21% of the Masaka cohort and just 18% of the Rakai cohort at the
same time. The overall proportions of young single people and the sex ratios were
therefore different between the cohorts.</p>
<p>There are several limitations to these analyses. We have combined data from repeated
cross-sectional DHS and two cohort studies. There may be selection biases in the
DHS, but these should not be present in the cohort studies.<xref ref-type="bibr" rid="b23">23</xref>
Different questionnaires were used for each data source. In
the Rakai study, AFS was only asked at the enrolment into the cohort at round 4 and
during rounds 6–10, so we have more information on some respondents.
However, this is entirely at random as recruitment to the cohort is not related to
first sex.</p>
<boxed-text position="float"><sec id="s4a1"><title>Take-home messages</title>
<list list-type="bullet"><list-item><p>Ugandan women born since the 1970s have started sex later than their
predecessors.</p>
</list-item>
<list-item><p>Change in men’s age at first sex has not been
directional.</p>
</list-item>
<list-item><p>Changes in age at first sex are unlikely to have contributed to the
initial decline in the prevalence of HIV in Uganda.</p>
</list-item>
</list>
</sec>
</boxed-text>
<p>Others have shown that the quality of reporting of AFS can be variable and
inconsistent, but this can be in either direction and should have no effect on the
overall estimates.<xref ref-type="bibr" rid="b18">18</xref>
All data may be affected
by social desirability bias as there have been extensive media campaigns in Uganda
promoting safe sex and abstinence, but this should be similar across all sources.
Although there have been health messages promoting abstinence and safe sex in
Uganda, we did not see any difference in the responses of the same birth cohort over
the four rounds of the DHS, which may indicate a limited bias due to social
desirability. This effect may be more pronounced in the two cohort studies where the
same people are seen every year and any messages would be reinforced over time, but
there is no evidence for this in the Masaka data.<xref ref-type="bibr" rid="b18">18</xref>
</p>
<p>A limitation of the cohort studies is the migration of young people from rural areas
after completion of school. In Masaka, most young people (especially girls) do not
remain at home, but either get married or migrate to larger towns or trading posts
to search for work. This may skew the proportion of sexually active young women that
remain in the cohort and may artificially raise the AFS if those who leave are never
recruited into the cohort and have a younger AFS than cohort members.</p>
<p>All three studies cover a large population, so the effects we see have tight
confidence limits and should give an accurate picture of any real changes in
reported AFS in Uganda. The three studies indicate that large changes in AFS have
been seen in women over the last 20 years. These changes may be influenced by the
HIV epidemic seen in Uganda, but are unlikely to be the factor which explains the
decline in HIV prevalence seen in Uganda in the 1990s. It is more likely that this
is a positive side effect of the empowerment of women, especially young women, so
that they can make their own choices about when and with whom they initiate sex.</p>
</sec>
</body>
<back><ack><p>The work in this paper was facilitated by a workshop run by the ALPHA network in
Zimbabwe. The authors thank the organisers of the workshop for the ideas and help
with the analysis and the writing of this paper. They also thank the project leaders
and all the staff of the study sites for their help and for the use of the data; the
participants in the studies and the communities for their forbearance and acceptance
of the studies; and Leigh Anne Shafer and Richard White for providing the HIV
prevalence data from the graphs in their papers.</p>
</ack>
<fn-group><fn fn-type="financial-disclosure"><p><bold>Funding:</bold>
The paper was written with financial support from the
Medical Research Council of UK, Johns Hopkins School of Public Health and the
Wellcome Trust through their support for the ALPHA network.</p>
</fn>
<fn fn-type="conflict"><p><bold>Competing interests:</bold>
None.</p>
</fn>
</fn-group>
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