Mortality Trends from 2003 to 2009 among Adolescents and Young Adults in Rural Western Kenya Using a Health and Demographic Surveillance System

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DOI: 10.1371/journal.pone.0047017 · Source: PubMed
Abstract
Background: Targeted global efforts to improve survival of young adults need information on mortality trends; contributions from health and demographic surveillance system (HDSS) are required. Methods and findings: This study aimed to explore changing trends in deaths among adolescents (15-19 years) and young adults (20-24 years), using census and verbal autopsy data in rural western Kenya using a HDSS. Mid-year population estimates were used to generate all-cause mortality rates per 100,000 population by age and gender, by communicable (CD) and non-communicable disease (NCD) causes. Linear trends from 2003 to 2009 were examined. In 2003, all-cause mortality rates of adolescents and young adults were 403 and 1,613 per 100,000 population, respectively, among females; and 217 and 716 per 100,000, respectively, among males. CD mortality rates among females and males 15-24 years were 500 and 191 per 100,000 (relative risk [RR] 2.6; 95% confidence intervals [CI] 1.7-4.0; p<0.001). NCD mortality rates in same aged females and males were similar (141 and 128 per 100,000, respectively; p = 0.76). By 2009, young adult female all-cause mortality rates fell 53% (χ(2) for linear trend 30.4; p<0.001) and 61.5% among adolescent females (χ(2) for linear trend 11.9; p<0.001). No significant CD mortality reductions occurred among males or for NCD mortality in either gender. By 2009, all-cause, CD, and NCD mortality rates were not significantly different between males and females, and among males, injuries equalled HIV as the top cause of death. Conclusions: This study found significant reductions in adolescent and young adult female mortality rates, evidencing the effects of targeted public health programmes, however, all-cause and CD mortality rates among females remain alarmingly high. These data underscore the need to strengthen programmes and target strategies to reach both males and females, and to promote NCD as well as CD initiatives to reduce the mortality burden amongst both gender.
Mortality Trends from 2003 to 2009 among Adolescents
and Young Adults in Rural Weste rn Kenya Using a Health
and Demographic Sur veillance System
Penelope A. Phillips-Howard
1
*, Frank O. Odhiambo
2
, Mary Hamel
3
, Kubaje Adazu
2{
, Marta Ackers
3
,
Anne M. van Eijk
1
, Vincent Orimba
2
, Anja van’t Hoog
2,4
, Caryl Beynon
5
, John Vulule
2
, Mark A. Bellis
5
,
Laurence Slutsker
3
, Kevin deCock
3
, Robert Breiman
2,6
, Kayla F. Laserson
2,6
1 Liverpool School of Tropical Medicine, Liverpool, United Kingdom, 2 KEMRI/CDC Research and Public Health Collaboration, Kisumu, Kenya, 3 Centers for Disease Control
and Prevention, Atlanta, Georgia, United States of America, 4 Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands, 5 Centre for Public Health,
Liverpool John Moores University, Liverpool, United Kingdom, 6 Centers for Disease Control and Prevention, Nairobi, Kenya
Abstract
Background:
Targeted global efforts to improve survival of young adults need information on mortality trends;
contributions from health and demographic surveillance system (HDSS) are required.
Methods and Findings:
This study aimed to explore changing trends in deaths among adolescents (15–19 years) and young
adults (20–24 years), using census and verbal autopsy data in rural western Kenya using a HDSS. Mid-year population
estimates were used to generate all-cause mortality rates per 100,000 population by age and gender, by communicable
(CD) and non-communicable disease (NCD) causes. Linear trends from 2003 to 2009 were examined. In 2003, all-cause
mortality rates of adolescents and young adults were 403 and 1,613 per 100,000 population, respectively, among females;
and 217 and 716 per 100,000, respectively, among males. CD mortality rates among females and males 15–24 years were
500 and 191 per 100,000 (relative risk [RR] 2.6; 95% confidence intervals [CI] 1.7–4.0; p,0.001). NCD mortality rates in same
aged females and males were similar (141 and 128 per 100,000, respectively; p = 0.76). By 2009, young adult female all-cause
mortality rates fell 53% (x
2
for linear trend 30.4; p,0.001) and 61.5% among adolescent females (x
2
for linear trend 11.9;
p,0.001). No significant CD mortality reductions occurred among males or for NCD mortality in either gender. By 2009, all-
cause, CD, and NCD mortality rates were not significantly different between males and females, and among males, injuries
equalled HIV as the top cause of death.
Conclusions:
This study found significant reductions in adolescent and young adult female mortality rates, evidencing the
effects of targeted public health programmes, however, all-cause and CD mortality rates among females remain alarmingly
high. These data underscore the need to strengthen programmes and target strategies to reach both males and females,
and to promote NCD as well as CD initiatives to reduce the mortality burden amongst both gender.
Citation: Phillips-Howard PA, Odhiambo FO, Hamel M, Adazu K, Ackers M, et al. (2012) Mortality Trends from 2003 to 2009 among Adolescents and Young Adults
in Rural Western Kenya Using a Health and Demographic Surveillance System. PLoS ONE 7(11): e47017. doi:10.1371/journal.pone.0047017
Editor: Ann M. Moormann, University of Massachusetts Medical School, United States of America
Received Jun e 13, 2012; Accepted September 11, 2012; Published November 5, 2012
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modi fied, built upon, or otherwise used by anyone for
any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Funding: The Health and Demographic Surveillance System (HDSS) and field staff support has been funded through the Centers of Disease Control infrastructure
grant, with supplemental support from project-specific grants. Funders had no role in study design, data collection and analysis, decision to publish, or
preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: pennyph@liverpool.ac.uk
{ Deceased
Introduction
While most global efforts to prevent mortality among young
people focus on children below 5 years of age, there are significant
health gains to be made among adolescent children and young
adults, however, targeted efforts for this are hampered by a lack of
data [1–3]. Of the estimated 2.6 million deaths occurring globally
among adolescents and young adults (AYA) in 2004, two out of
three deaths were in sub-Saharan Africa (SSA) and south-east Asia
[1]. SSA has the highest AYA mortality rates for maternal,
communicable disease, non-communicable disease, and injuries
for both genders [1]. For example, among an estimated 10 million
AYA aged 15–24 years living with HIV globally, 62% live in SSA
[1,3–6]. In 2004, disability adjusted life-years, comprising years of
life disability as well as years of life lost, were 2.5 times higher in
AYA aged 10–24 years in SSA compared with worldwide, and
substantially higher than other low and middle income countries
[3]. Further, in SSA, disability adjusted life-years comprise an
equal proportion of years of life lost and years of life disability,
whereas other regions mostly represent years of life disability [3].
Aggregated international data suggest mortality rates among AYA
in SSA vary by age, but generally rates rise after early adolescence
(10–14 years) and peak in young adulthood (20–24 years) [1].
Among young females, mortality is reportedly due to the burden of
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sexual and reproductive health threats, while injuries predominate
among young males [1–4,6].
Concern has been raised on the underinvestment in public
health interventions for adolescents and young adults, and that
investment for prevention against some threats, such as injuries,
have fallen behind HIV/AIDS and reproductive health [3,7,8].
While a number of recent publications explored changing trends
in all-cause and disease-specific mortality in adults in SSA [9–14],
there is a dearth of literature on mortality ascertainment among
AYA [15]. If global health targets are to include a stronger focus
on the wider health concerns of AYA, longitudinal data would be
helpful to define the needs and priorities, and how they evolve and
are impacted by interventions. Quantification of various causes of
death is imprecise in low and middle income countries,
particularly in SSA, and sharing of available data for public
health benefit is advocated [16]. Verbal autopsy, generated in
subpopulations covered by health and demographic surveillance
systems (HDSS) and standardised through the International
Network for the Demographic Evaluation of Populations and
Their Health in Developing Countries (INDEPTH), forms an
important basis for mortality ascertainment in rural SSA [17].
INDEPTH is a global network of members who conduct
longitudinal health and demographic evaluation of populations
in low- and middle-income countries [18]. Data generated from
the Kenya Medical Research Institute (KEMRI)/US Centers for
Disease Control and Prevention (CDC) HDSS research site in
rural western Kenya [19,20], an INDEPTH Network member,
provide local data to inform planning of programmes directed at
health issues affecting the population. Data from the KEMRI/
CDC HDSS have been utilised to examine the impact of TB
disease on mortality [9], and HIV care and treatment service
uptake on adult population-level mortality [14]. HDSS data were
also examined to explore trends and characteristics of under-5
child mortality between 2003 and 2009 [21]. In this study, we aim
to utilise HDSS data to explore the characteristics and trends in
mortality, specifically among the highest risk AYA, aged 15–24
years, to identify changes in mortality in an area with expanding
HIV treatment and care services, and discuss implications for
public health programmes.
Materials and Methods
Study Site and Population
During the study period, the KEMRI/CDC HDSS study site
was located in a rural part of Nyanza Province in western Kenya
in Asembo (Rarieda District) and Gem (Yala and Wagai
Divisions), Siaya District [19,20,22]. The area included 217
villages spread over a 500 km
2
area along the shores of Lake
Victoria, with a mid-year population of 136,448 in 2003 rising to
146,081 by 2009. Among AYA aged 15–24 years, the gender
breakdown is relatively equal, with a mean (annually fluctuating)
mid-year annual population of 14,780 males and 14,502 females
(total 29,282). The population, mainly subsistence farmers, are
almost exclusively members of the Luo ethnic group and have
been described in detail elsewhere [19,22,23]. Inhabitants live in
family compounds comprising one or more (average 2.1) houses
surrounded by their land. The society is polygynous with
approximately a third of males having more than one wife [23].
The population is impoverished with a mean ‘wealth index’
previously estimated to be $600 to $700 per compound [24]. HIV
[5,25–27], TB [9,28–30], malaria [31–34], schistosomiasis [35–
37], and suboptimal water quality, sanitation and hygiene [38–41],
are leading causes of morbidity and mortality within the study
area.
Health and Demographic Surveillance System (HDSS)
The population was registered and households were geo-
spatially located during an insecticide treated bednet trial [22].
The HDSS site was registered in 2001 as a member of the
INDEPTH Network [19,20]. A household census is conducted
throughout the study area tri-annually to capture births, pregnan-
cies, deaths, in- and out- migration, and economic data. These
data provide mid-year population denominators, stratified by age
group and gender.
Verbal Autopsy (VA)
All resident deaths reported to field staff during census are
followed up with a visit to households to validate deaths and
record events surrounding death, using a standardized verbal
autopsy (VA) questionnaire. Residents are defined as all persons
residing in the study site for 4 months or more, precluding
transient residents and visitors. VA is conducted using standard-
ised WHO questionnaires endorsed by INDEPTH, for all deaths
occurring in the HDSS [18,20]. For this analysis, we utilized the
adult questionnaire (15 years and above). A previous one year
review of deaths examined data from 2003 and describes the VA
methodology in detail [42]. Resident identification numbers allow
linkage of each death with HDSS data. Parents or spouses are
identified as the first respondents. VA interviews are performed, at
least one month (average 3 months) after the death to respect the
mourning period, while still facilitating recall. Absence of an adult
in the home is recorded as a non-VA interview, enabling only
verification that death occurred and collection of minimal
demographic indices. VA forms are reviewed independently by
at least two clinical officers and cause of death assigned. In 2006,
‘‘Sample Vital Registration with Verbal Autopsy (SAVVY)’’ was
adopted at the KEMRI/CDC HDSS (and across INDEPTH sites)
to strengthen vital event monitoring and measurement. SAVVY
constitutes a resource library of best practice to improve the
quality of civil registration, harmonized to the WHO International
Classification of Disease [43]. This facilitated attribution of the
cause of death.
Ethical Considerations
Following cultural customs, compound heads provide written
consent for all compound members to participate in the HDSS
activities. Any individual can refuse to participate at any time. The
HDSS protocol and consent procedures, including surveillance
and VA activities, were approved by KEMRI (#1801) and CDC
Institutional Review Boards (#3308). All HDSS census and VA
data are maintained on a secure server with access only by
authorized researchers. Named data are securely stored in a MS-
SQL database and only authorized data personnel have access
rights. Datasets used by scientists for analysis are stripped of names
to protect identity.
Analyses
Data were extracted from the HDSS database for all deaths
occurring among residents aged between 15 to 24 years of age at
the time of death, between January 2003 and December 2009.
Data transformation and analyses were conducted using SPSS for
Windows (Release v18.0), and EpiInfo Stat Calc (CDC Atlanta,
USA). Analyses on proportions and rates per 100,000 population
were conducted on all-cause; and grouped into communicable
disease (CD), and non-communicable disease (NCD) causes. The
category of NCD included injuries, maternal (including septicae-
mia), cancers and nutritional causes.
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Mean age of death among all AYA aged 15–24 years is
presented with standard deviation (SD), for all-cause mortality by
gender, and for key diseases. Analyses are stratified into
adolescence (15–19 years old) and young adulthood (20–24 years
old). Mortality rates per 100,000 were estimated by year and age
category, using mid-year population-point estimates generated
from the HDSS census. Dates of death were grouped per year to
facilitate calculation of annual mortality rates per age category and
by gender. Key social and demographic characteristics generated
through the HDSS for analyses here included marital status (ever
married; divorced or widowed at time of death), place of death
(home or health facility; comprising clinic, hospital, on route to/
from health facility); education (attended and completed primary
school), and socio-economic status (SES). Routinely collected SES
indicators such as occupation of household head, primary source
of drinking water, use of cooking fuel, in-house assets (e.g., lantern
lamp, sofa, bicycle, radio, TV) and livestock (poultry, pigs, donkey
cattle, sheep, goats) [24], were used to calculate an SES index as a
weighted average using multiple correspondence analysis [44].
This ranked households into SES quintiles with the first quintile
representing the poorest and the fifth representing the least poor;
for some analyses this was collapsed into most (1–2) and less (3–5)
poor.
Analyses to examine trends in mortality rates per 100,000
population over time were conducted for all-cause, CD and NCD
sub-strata. Chi-squared (x
2
) test for linear trend determined the
statistical significance of changing rates by gender over time (2003
to 2009). Differences between groups were determined using
Pearson’s x
2
test, and the level of significance was set at 5% or less.
Mantel-Haenszel Relative Risks (RR), with Taylor Series 95%
confidence intervals (CI), was used to compare mortality rates
between genders, by year of death. Unless stated, RR compares
female to male rates; where rates are significantly higher for males,
reciprocal values are given (RR
male
).We stratified RR analyses for
mortality rates into the two age groups, by gender, by year for all-
cause, CD, and NCD mortality, generating a summary x
2
, with a
MH weighted RR and Greenlands-Robins 95% CI.
Results
Socio-demographics
Of 12,041 documented deaths occurring during the study
perio d in adults aged 15 years and above in Asembo and Gem,
967 (8.0%) were among AYA (n = 293, 30.3% 15–19 years;
n = 674, 69.7% 20–24 year s, table 1). Females constituted two-
thirds (651; 67.3%) of deaths. Young adult f emales (20–24 years)
were disproportionately repre sented, compris ing three qu arters
(75.3 %) of all female deaths. The mean age of death of all AYA
deaths was 21 .3 years (standard deviation; SD 2.7 years). Just
over a third of deaths were in the two lowest SES quintiles, with a
higher proportion of females (39.3%) than males (31.4%)
represented (relative risk [RR] 1.25; 95% confidence intervals
[CI] 1.0–1.5, table 1); this compares with 28% and 25% in
femal es and males, aged 18–24 years within the population (data
not shown). Significantly m ore females (60.8%) had been ever
married compared with males (22.5%; RR 2.7, 95% CI 2.1–3.4).
Howev er, among tho se AYA who had ever been married, 26.9%
were divorced or separated at the time of their death, with no
Table 1. Characteristics of deaths
a
in late adolescents and young adults aged 15 to 24 years, documented through verbal
autopsy.
Variable N
b
Value Female (%) Male (%) Total (%) RR
fem
(95% CI) x
2
p value
Age 967 15–19y 161 (24.7) 132 (41.8) 293 (30.3) 0.59 (0.49–0.71) 29.25 ,0.001
20–24y 490 (75.3) 184 (58.2) 674 (69.7)
Area 967 Asembo 272 (41.8) 125 (39.6) 397 (41.1) 1.06 (0.90–1.24) 0.44 0.509
Gem 379 (58.2) 190 (60.4) 570 (58.9)
SES
c
909 MCA
c
1–2 241 (39.3) 93 (31.4) 334 (36.7) 1.25 (1.03–1.52) 5.35 0.021
MCA
c
3–5 372 (60.7) 203 (68.6) 575 (63.6)
Ever Married 814 Yes 330 (60.8) 61 (22.5) 391 (48.0) 2.70 (2.14–3.40) 106.4 ,0.001
No 213 (39.2) 210 (77.5) 423 (52.0)
Divorced
d
346 Yes 74 (25.8) 19 (32.2) 93 (26.9) 0.80 (0.53–1.22) 1.03 0.311
No 213 (74.2) 40 (67.8) 253 (73.1)
Widowed 391 Yes 43 (13.0) 2 (3.3) 45 (11.5) 3.97 (0.99–16.0) 4.81 0.028
No 287 (87.0) 59 (96.7) 346 (88.5)
Primary School 642 Attend yes 381 (90.9) 203 (91.0) 584 (91.0) 0.99 (0.95–1.05) 0.00 0.966
Attend no 38 (9.1) 20 (9.0) 58 (9.0)
Secondary School 788 Attend yes 65 (12.4) 38 (14.3) 103 (13.1) 0.87 (0.60–1.26) 0.57 0.452
Attend no 458 (87.6) 227 (85.7) 685 (86.9)
Place Died 818 Home 406 (74.4) 189 (69.5) 595 (72.7) 1.07 (0.98–1.17) 2.18 0.140
+HHF
e
140 (25.6) 83 (30.5) 223 (27.3)
NOTE. RR
fem
, Relative risk for females compared with males; CI, confidence interval; x
2
, chi-squared.
a
All-cause mortality, includes persons who died with no cau se of death allocated (undetermined).
b
Numbers vary due to missing data (for example, a relative’s non-response), or within categories such as divorced or widowed among those reportedly ever married.
c
Socio-economic status (SES) defined through Multiple Correspondence Analysis (MCA) wealth quintiles 1 = poorest 5 = least poor, ranking then collapsed into 1–2
(most poor), 3–5 (less poor).
d
Divorced or separated from partner at time of death, denominator restricted to those reportedly ever married.
e
+HHF represents place of death in hospital, health facility, or to/from HHF.
doi:10.1371/journal.pone.0047017.t001
Mortality in Adolescents and Young Adults
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significant difference by gender. This compares with a divorce
rate of ,5% among those 18–24 years in the population (data not
shown). Among ever married, a further 11.5% were widowed at
the time of their death; here there was a strong association with
gender, with 13.0% of females compared with just 3.3% of m ales
repor ted to have been widowed (RR 3.97; 95% CI 1.0–16.0).
Widowhood among the general population in this age group is
rare, with rates recorded of 2% and 1% among females and
males aged 18–24 years (data not shown). Of 642 with reported
primary school status, 91% of d eaths in both gender had attended
school, however, less than half (46.6%; 49.6% of females and
40.8% of males, p = 0.033) completed their primary school
education. Only 13.1% attended second ary school, with no
significant differ ence by gender (table 1). The majority (72.7%) of
AYA died at home, among both males (69.5%) and females
(74.4%).
Causes of Death
Ascribed cause of death was available for 793 (82.1%) of 967
deaths. Among the 174 deaths with no cause determined, age,
gender, SES and place of death were comparable with deaths
attributed to a cause. Among those with a cause, 70.0% fell within
the communicable disease classification, and 30.0% were classified
with a non-communicable disease (figure 1).
Communicable diseases (CD). CD included HIV, TB,
malaria and other infections (figure 1a). Three quarters (76.8%) of
deaths among females, compared with a half (56.6%) of male
deaths were from a CD (table 2). This largely reflects the burden of
HIV, identified as the primary cause in 281 (35.4%) of all deaths,
and 50.6% of CD deaths. HIV was attributed to 41.8% of all
female and 22.8% of all male deaths, and constituted 54.5% and
40.4% of female and male CD deaths, respectively. AYA females,
thus, had close to a two-fold (RR 1.8, 95% CI 1.4–2.3) higher
Figure 1. Number of deaths by primary cause in adolescents and young adults, 2003–2009, by primary cause and gender. A,
Communicable diseases; B, Non-communicable diseases. Note axis change between Figure 1A and Figure1B.
doi:10.1371/journal.pone.0047017.g001
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proportion of deaths attributed to HIV compared with males.
Malaria was reported as the second overall leading cause of death,
in 13.4% of all deaths, constituting 19.1% of CD deaths, with no
gender difference. TB was categorized as the direct cause in 13.0%
of all deaths, constituting 18.6% of all CD deaths, with a higher
proportion among females compared with males (15.4% versus
8.2%; p = 0.005). HIV and TB combined constituted 69.2% of all
CD deaths and 48.0% of all attributed AYA deaths; contributing
57.2% of all female and 31.1% of all male diagnosed deaths (RR
1.8, 95% CI 1.5–2.2). Other infections contributed to 11.7% of
CD deaths and to 8.2% of all ascribed causes of death. More male
(11.6%) than female (6.5%) deaths were from ‘other infections’
(RR
male
1.8, 95% CI 1.1–2.9). Among ‘‘other infections’’, most
common were meningitis (40%), pneumonia (29.2%), gastro-
enteritis/dysentery/cholera (18.5%), typhoid and paratyphoid
(6.2%), sepsis (4.6%), and rheumatic heart disease (1.5%).
Non-communicable diseases (NCD). Deaths attributed to
injuries (8.4% of all diagnosed causes) were predominantly among
males (figure 1b), with 52 of 67 injuries (77.6%; RR
male
6.8; 95%
CI 3.9–11.9; table 2), and ranked as the overall second highest
cause among males after HIV (19.5% of all male deaths, and
44.8% of all male NCD deaths). Injuries were ascribed to
poisonings/other trauma (47.8%), accidents (25.4%), assault
(16.4%), and suicides (10.4%). Six of the seven recorded suicides
Table 2. Main causes of death
a
among adolescents and young adults (15–24 years), by gender.
Cause Female (%) n = 526 Male (%) n = 267 Total (%) n = 793 RR
fem
(95% CI) x
2
p value
CD
b
Yes 404 (76.8) 151 (56.6) 555 (70.0) 1.36 (1.21–1.52) 34.6 ,0.001
No 122 (23.2) 116 (43.4) 238 (30.0)
HIV/TB
c
Yes 301 (57.2) 83 (31.1) 384 (48.4) 1.84 (1.52–2.23) 48.5 ,0.001
No 225 (42.8) 184 (68.9) 409 (51.6)
HIV Yes 220 (41.8) 61 (22.8) 281 (35.4) 1.83 (1.44–2.33) 27.9 ,0.001
No 306 (58.2) 206 (77.2) 512 (64.6)
TB Yes 81 (15.4) 22 (8.2) 103 (13.0) 1.87 (1.20–2.92) 8.03 0.005
No 445 (84.6) 245 (91.8) 690 (87.0)
Malaria Yes 69 (13.1) 37 (14.3) 106 (13.4) 0.95 (0.65–1.37) 0.08 0.77
No 457 (86.9) 230 (86.1) 687 (86.6)
Oth.Infections Yes 34 (6.5) 31 (11.6) 65 (8.2) 0.56 (0.35–0.89) 6.23 0.013
No 492 (93.5) 236 (88.4) 728 (91.8) [1.80(1.13–2.86)]
d
Injuries Yes 15 (2.9) 52 (19.5) 67 (8.4) 0.15 (0.08–0.26) 63.3 ,0.001
No 511 (97.1) 215 (80.5) 726 (91.6) [6.85 (3.92–11.9)]
CNS Yes 18 (3.4) 28 (10.5) 46 (5.8) 0.33 (0.18–0.58) 16.2 ,0.001
No 508 (96.6) 239 (89.5) 747 (94.2) [3.06 (1.73–5.43)]
Nutritional Yes 24 (4.6) 8 (3.0) 32 (4.0) 1.52 (0.69–3.34) 1.12 0.289
No 502 (95.4) 259 (97.0) 761 (96.0)
Maternal Yes 34 (6.5) ––– 34 (4.3) 18.0 ,0.001
No 492 (93.5) 267 (100 ) 759 (95.7)
Respiratory Yes 4 (0.8) 1 (0.4) 5 (0.6) 2.03 (0.23–18.08) 0.42 0.516
No 522 (99.2) 266 (99.6) 788 (99.4)
Gut Yes 4 (0.8) 4 (1.5) 8 (1.0) 0.51 (0.13–2.01) 1.97 0.326
No 522 (99.2) 263 (98.5) 785 (99.0)
Liver Yes 4 (0.8) 6 (2.2) 10 (1.3) 0.34 (0.10–1.19) 3.14 0.076
No 522 (99.2) 261 (97.8) 783 (98.7)
Cancer Yes 4 (0.8) 3 (1.1) 7 (0.9) 0.68 (0.15–3.02) 0.27 0.605
No 522 (99.2) 264 (98.9) 786 (99.1)
Cardio-vascular Yes 4 (0.8) 3 (1.1) 7 (0.9) 0.68 (0.15–3.02) 0.27 0.605
No 522(99.2) 264 (98.9) 786 (99.1)
Renal/Urinary Yes 2 (0.4) 4 (1.5) 6 (0.8) 0.25 (0.05–1.38) 2.93 0.086
No 524 (99.6) 263 (98.5) 787 (99.2)
Diabetes Yes 1 (0.2) 2 (0.7) 3 (0.4) 0.25 (0.02–2.79) 1.47 0.226
No 525 (99.8) 265 (99.3) 790 (99.6)
NOTE. RR
fem
, Relative risk for females compared with males; CI, confidence interval; x
2
, chi-squared.
a
Statistics presented exclude deaths with undetermined cause (n = 174); of 238 NCD deaths, 13 ‘other’ NCDs are excluded from main cause of death analysis.
b
CD, communicable diseases (HIV, TB, malaria, other common infections).
c
HIV/TB is the combination of all deaths diagnosed with either TB or HIV as the cause of death.
d
Significantly higher proportion of deaths in males, inverse RR
males
presented [in brackets].
doi:10.1371/journal.pone.0047017.t002
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were male. For females, deaths directly attributed to pregnancy
and childbirth contributed a quarter (24.6%) of their NCD
burden, with 6.5% of all female deaths overall ascribed maternal
death as the prime cause. Reported causes were puerperal sepsis
(29.4%), ante- or post-partum haemorrhage (17.6%), eclampsia
(14.7%), abortion/miscarriage (11.8%), obstructed labour (8.8%),
and ‘other complications’ (17.6%). Mortality attributed to a
central nervous system (CNS) cause was predominantly (93.5%)
attributed to seizures/epilepsy. Of the remaining NCD deaths,
other disorders associated with hepatic (hepatic unspecified),
respiratory (asthma), renal (nephrotic syndrome, renal failure),
gut (obstruction, symptoms of abdomen/pelvis), or cardio-vascular
(congestive cardiac failure), disorders each contributed ,5% of the
deaths among AYA (table 2).
Changing Patterns of Mortality
All-cause mortality rates. Between 2003 and 2009, the
absolute number of deaths recorded annually decreased from 179
in 2003 to 111 in 2009. While the number of female deaths halved
from 124 to 61, male deaths fell only marginally (from 55 to 50),
resulting in the overall ratio of male to female deaths changing
from 0.44 (55:124) in 2003 to 0.82 (50:61) by 2009. There was a 2-
fold higher all-cause mortality rate among 15–24 year old females
compared with same aged males in 2003 (RR 2.2; 1.6–3.1; table 3).
Rates were significantly higher among females in both age groups.
Annual all-cause mortality rates fell significantly from 2003 to
2009 among females but not males (table 3). Rates halved from
874 to 414 per 100,000 population for all AYA females, showing a
significant linear trend, while a 14% reduction among males was
not significant. Mortality reduction was significant among young
adult females, reducing 53% from 1,613 to 754 per 100,000. In
same aged males, deaths fell 33% from 716 to 482 but with no
significant linear trend. By 2009, all-cause mortality rates were no
longer significantly different by gender. Among adolescents, while
all-cause mortality rates fell significantly among females by 61.5%,
from 403 to 155 per 100,000, mortality rates were static for same
aged males. This resulted in the rate of mortality among
adolescent females dipping below that of males in 2009 (155 and
240 per 100,000, respectively), with no significant difference in
mortality rates by gender in that year (table 3).
Table 3. Trends in all-cause mortality rates per 100,000 by gender and age group.
Female MR
a
Male MR
a
RR
fem
(95% CI) x
2
P value M:F Ratio
15–24y 2003 874 390 2.24 (1.63–3.08) 26.4 ,0.001 0.45
2004 796 307 2.59 (1.83–3.67) 31.2 ,0.001 0.39
2005 661 281 2.35 (1.63–3.39) 22.2 ,0.001 0.43
2006 642 310 2.07 (1.45–2.95) 17.0 ,0.001 0.48
2007 656 224 2.93 (1.98–4.32) 32.0 ,0.001 0.34
2008 466 298 1.56 (1.08–2.27) 5.70 0.017 0.64
2009 414 334 1.24 (0.85–1.80) 1.28 0.26 0.81
x
2
LT
b
34.14 0.99 MHRR
c
2.08 (1.82–2.38); Summary x
2
121.55; p,0.001
P value ,0.001 0.33
15–19y 2003 403 217 1.86 (1.08–3.22) 5.1 0.02 0.54
2004 323 238 1.36 (0.78–2.37) 1.2 0.28 0.74
2005 292 138 2.11 (1.08–4.13) 5.0 0.25 0.47
2006 255 217 1.18 (0.64–2.17) 0.3 0.60 0.85
2007 262 194 1.35 (0.73–2.52) 0.9 0.34 0.74
2008 197 180 1.09 (0.56–2.14) 0.1 0.79 0.91
2009 155 240 0.65 (0.33–1.28) 1.6 0.21 1.55
x
2
LT
b
11.94 0.001 MHRR
c
1.33 (1.06–1.67); Summary x
2
5.65; p = 0.02
P value ,0.001 0.97
20–24y 2003 1613 716 2.25 (1.53–3.32) 17.7 ,0.001 0.44
2004 1540 433 3.56 (2.23–5.68) 32.5 ,0.001 0.28
2005 1217 541 2.25 (1.45–3.49) 14.0 ,0.001 0.44
2006 1166 465 2.51 (1.60–3.92) 17.4 ,0.001 0.40
2007 1186 273 4.34 (2.53–7.45) 34.1 ,0.001 0.23
2008 817 484 1.69 (1.08–2.65) 5.3 0.02 0.59
2009 754 482 1.57 (0.98–2.49) 3.6 0.06 0.64
x
2
LT
b
30.40 2.73 MHRR
c
2.43 (2.05–2.88); Summary x
2
112.8; p,0.001
P value ,0.001 0.10
NOTE. RR
fem
, Relative risk for females compared with males; CI, confidence interval; x
2
, chi-squared.
a
MR, mortality rates per 100,000, note all-cause mortality includes deaths with undetermined cause, and are thus higher than combined communicable and non-
communicable disease mortality rates.
b
x
2
LT, chi-squared for linear trend.
c
MHRR, Mantel Haenszel weighted relative risk, and Greenlands-Robins 95% confidence intervals.
doi:10.1371/journal.pone.0047017.t003
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Communicable disease mortality rates. In 2003, CD
mortality rates were over two and a half times higher among
female AYA compared with males (500 versus 191 per 100,000;
RR 2.6; 1.7–4.1; table 4; figure 2). By 2009 there had been a two-
fold reduction among females, with rates halving significantly from
500 to 224 per 100,000 (figure 2a). This fall was not mirrored
among males with rates decreasing non-significantly by 27% from
191 to 140 per 100,000 (figure 2b). In adolescents, CD mortality
rates fell for both genders (69% females, 44.5% for males); the
drop was statistically significant for females (x
2
for linear trend
8.75; p = 0.003), but not for males. Among young adults, CD
mortality rates halved among females from 924 to 440 per 100,000
(x
2
for linear trend 15.0; p,0.001), but for same aged males, the
fall of 21% from 327 to 258 per 100,000 was not associated with a
significant linear trend. The fall in rates among females, together
with marginal changes among males, resulted in no significant
differences in CD mortality rates between females and males,
overall, and by each age group by 2009 (table 4), although rates for
females still exceeded those of males. The ratio of male to female
CD mortality rates changed from 0.38 in 2003, to 0.61 by 2009.
Non-communicable disease mortality rates. Two main
causes of death for NCD were injuries in males and maternal
causes among females. NCD mortality rates in males and females
showed no significant trends by year or by gender (figure 3).
Including maternal mortality, the NCD-attributed mortality rate
for AYA females aged 15–24 years ranged between 56 and 169 per
100,000 (table 5; figure 3a). There was no evidence of linear
change in mortality rates over time. While NCD mortality rates for
young adult females fell 53.7% from 272 to 126 per 100,000
between 2003 and 2009, the linear trend was not significant.
Similar rates were recorded for males, with a comparable range as
for females in both age groups (table 5), with no significant
Figure 2. Communicable disease mortality rates in adolescents and young adults, 2003–2009, by primary cause. A, Female; B, Male.
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difference in rates by gender. Rates among males fluctuated over
time with no significant trend in overall rates (figure 3b). By 2009,
mortality rates associated with injury equalled HIV as the top
cause of death among males (figure 4), and rose among females to
constitute the 3
rd
leading cause of death (figures 4a, 4b). The ratio
of male to female NCD mortality rates changed from 0.91 in 2003,
to 1.47 by 2009.
Discussion
Despite calls to strengthen public health measures for adoles-
cents and young adults, particularly for sub-Saharan Africa (SSA),
publications examining mortality rates in persons over 15 years
have aggregated adult age, preventing evaluation of the specific
changes occurring among adolescents and young adults. Data
presented here were generated from a longitudinal, consistently
maintained, health and demographic surveillance system in a rural
area of western Kenya, facilitating comparison by age and gender
over time, broken down into communicable and non-communi-
cable disease causes. We found significant reductions in all-cause
and communicable disease mortality among all female AYA (aged
15–24 years) between 2003 and 2009; however, no reductions
were found among same aged males, or for non-communicable
diseases in either gender.
All-cause mortality rates halved among female AYA aged 15–24
years between 2003 and 2009. The very high burden of mortality
among this population is demonstrated by comparison with the
average all-cause mortality rates estimated for young women in
SSA in global burden of disease (GBD) studies [1]. The average
all-cause mortality rate for females aged 20–24 years in SSA was
522 per 100,000 in the GBD study for 2004, three-fold lower than
the 1,540 per 100,000 calculated for same aged females in western
Kenya in the same year (table 3). Even by 2009, when rates had
halved to 754 per 100,000 in our western Kenya site, rates were
still higher than the GBD 2004 estimated average [1].
In our analyses, three-quarters of female deaths were ascribed to
communicable diseases, predominantly HIV. The prevalence of
HIV among adults in Kenya was estimated to be around 7% in
2007. Nyanza Province (which includes our study site), bears the
highest burden at 14.9% [45]. HIV sero-prevalence in females was
found to rise rapidly during adolescence; in the HDSS study area
Table 4. Trends in communicable disease mortality rates per 100,000 by gender and age group.
Female MR
a
Male MR
a
RR
fem
(95% CI) x
2
P value M:F Ratio
15–24y 2003 500 191 2.61(1.68–4.07) 19.6 ,0.001 0.38
2004 472 174 2.71 (1.71–4.28) 19.7 ,0.001 0.37
2005 415 130 3.18 (1.90–5.33) 21.6 ,0.001 0.31
2006 447 169 2.65 (1.67–4.20) 18.5 ,0.001 0.38
2007 458 73 6.31 (3.34–11.9) 42.3 ,0.001 0.16
2008 276 149 1.85 (1.11–3.08) 5.8 0.016 0.54
2009 231 140 1.65 (0.96–2.83) 3.3 0.07 0.61
x
2
LT
b
17.80 2.40 MHRR
c
2.73 (2.26–3.28); Summary x
2
119.28; p,0.001
P value , 0.001 0.12
15–19y 2003 230 119 1.93 (0.93–4.03) 3.2 0.07 0.52
2004 150 130 1.16 (0.53–2.53) 0.1 0.72 0.87
2005 164 43 3.85 (1.27–11.8) 6.6 0.01 0.26
2006 133 108 1.23 (0.52–2.90) 0.2 0.63 0.81
2007 167 43 3.88 (1.28–11.8) 6.7 0.01 0.26
2008 69 63 1.09 (0.35–3.39) 0.02 0.88 0.91
2009 72 66 1.09 (0.35–3.39) 0.02 0.88 0.92
x
2
LT
b
8.75 3.48 MHRR
c
1.73 (1.22–2.43); Summary x
2
9.39; p = 0.002
P value 0.003 0.06
20–24y 2003 924 327 3.07 (1.73–5.45) 16.4 ,0.001 0.35
2004 979 256 3.82 (2.09–7.00) 22.0 ,0.001 0.26
2005 794 290 2.74 (1.53–4.91) 12.5 ,0.001 0.37
2006 870 268 3.24 (1.83–5.75) 18.3 ,0.001 0.31
2007 849 119 7.11 (3.24–15.6) 32.6 ,0.001 0.14
2008 545 284 1.92 (1.08–3.41) 5.1 0.02 0.52
2009 440 258 1.64 (0.88–3.09) 2.4 0.12 0.59
x
2
LT
b
14.96 0.71 MHRR
c
2.99 (2.38–3.74); Summary x
2
98.49; p,0.001
P value , 0.001 0.40
NOTE. RR
fem
, Relative risk for females compared with males; CI, confidence interval; x
2
, chi-squared.
a
MR, mortality rates per 100,000; includes deaths ascribed to HIV, TB, malaria, and other infections (meningitis, pneumonia, gastro-intestinal, typhoid/paratyphoid,
sepsis, and rheumatic heart disease).
b
x
2
LT, chi-squared for linear trend.
c
MHRR, Mantel Haenszel weighted relative risk, and Greenlands-Robins 95% confidence intervals.
doi:10.1371/journal.pone.0047017.t004
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the prevalence among 13–14 year olds was 1.3%, rising to 12.8%
by 17 years of age [5], and was 10-fold higher in young females
compared with same aged males [5]. Exposure of young females to
HIV from older male partners [46], results in a high prevalence of
HIV infected female widows [47]. In the study area female but not
male widowhood was strongly associated with HIV [5]. In our
study, 13% of AYA females who died were widowed compared
with 3.3% of males. HIV-related deaths in SSA had peaked in
2004, declining by 20% by 2009, in tandem with the scaling up of
interventions such as provision of antiretroviral therapy (ART)
[48,49]. In Kenya, overall AIDS-related deaths fell 29% between
2002 and 2007 [45]; in the HDSS study area, all-cause and AIDS/
TB-associated mortality in adults declined 34% and 26%,
respectively, between 2003 and 2008 [14]. During that period,
HIV treatment and care centres expanded from 1 to 17, with a
corresponding increase in HIV services among HIV-positive
HDSS residents [14], with a higher proportion of females to males
enrolled in the HIV clinic services. In our current analyses, in the
same HDSS study area, all-cause and CD associated mortality
among young females halved suggesting successful targeting of
this population group from expanded HIV services. In contrast,
the small and non-significant decline in all-cause and CD
associated mortality among young men suggest that considerations
for mortality are complex, and that young males may not have
Figure 3. Non-communicable disease mortality rates in adolescents and young adults, 2003–2009, by primary cause. A, Female; B,
Male. Causes of death aggregated.
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benefited as much as females from the strengthening of HIV-
related services. Earlier infection and treatment seeking among
females may have resulted in better identification and access to
ART leading to a decrease in mortality. Lessons from interven-
tions which successfully signposted young women into HIV-related
services, such as antenatal care and the prevention of mother to
child HIV transmission [50–52], may also contribute to more
successful intervention leading to reduced mortality. For males,
programmes need to increase their efforts to identify young HIV-
infected men earlier by expanding access to HIV testing, and more
importantly to provide them with preventive services (i.e.,
voluntary medical male circumcision, condoms, STI diagnosis
and treatment, etc.) to prevent HIV acquisition. While there was
no routine system for generating laboratory-confirmed HIV status
among deaths in our population during the study period, current
door-to-door HIV testing within the HDSS and future studies on
HIV service delivery and HIV associated mortality will allow us to
strengthen future analyses and interpretation of the effectiveness of
services.
A number of studies have shown mortality reductions among
adults in countries of SSA during recent years [10–13], but
without describing specific reductions among AYA. In Ethiopia,
AIDS deaths declined by 21.9 and 9.3% for adult males and
females aged 20–64 years, respectively, between 2001 and 2005,
and by 38.2 and 42.9% for males and females between 2005 and
2007 [10]. The study explored cause of death recorded in the
burial records, a traditional system used in many countries in SSA
to register deaths occurring outside of hospital, and calculated a
reduction in AIDS deaths in 2007 to be between 56.8% and
63.3%, compared with the expected number in the absence of
ART [10]. In Malawi, there was a highly significant linear
downward trend in death rates between 2000 and 2007, with a
mean annual incremental death rate reduction of 0.52 per 1,000
population per year [12]. Another study, utilising verbal autopsy,
demonstrated significant reductions in all-cause and HIV-specific
mortality between 2003 and 2009 among South African adults
aged 15–49 years but did not disaggregate by age or gender [13].
Figure 4. Mortality rates by top primary causes in 2003, 2006 and 2009. A, Female; B, Male. Causes of death aggregated.
doi:10.1371/journal.pone.0047017.g004
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We have been reticent, in interpreting our data, to place too
much credence on cause-specific mortality rates. While an
inexact science, verbal autopsy remains one of the only
currently available feasible tools to ascribe cause to deaths
occurring in community settings in low and middle income
countries [53]. Our VA documented that seven in every ten
deaths among AYA in the HDSS study site occurred in the
home, and of the remainder, the majority dying in hospital
were associated with trauma in males. In our study, the
majority of deaths were ascribed to communicable diseases, and
specifically to HIV. In Ethiopia, VA for diagnosing AIDS
mortality had a high sensitivity (0.82) and specificity (0.76) when
compared with hospital records reporting HIV serostatus [11].
The model performed better for TB/AIDS combined with a
sensitivity and specificity of 0.91 and 0.78, respectively [11]. In
Zimbabwe 69% of deaths were accurately ascribed to AIDS/
non-AIDS through verbal autopsy [54]. Deaths ascribed to TB
and malaria may have been misclassified or have represented
co-infection with HIV [28,55]. Co-morbidity between HIV and
TB is well described in the HDSS study area; among a
prevalence of 6 per 1,000 pulmonary TB cases in adults of 15
years and older, half tested were found to be HIV positive [29].
Excess mortality in persons 15 years and older who were
treated for TB between 2006 and 2008 and HIV infected, was
2-fold higher compared with same aged persons who were HIV
infected who did not have TB, when adjusted for age and sex
[9].
Understanding the relationship between malaria infection and
the 13% of AYA deaths ascribed to this cause is not straightfor-
ward. Early adult VA studies had a low sensitivity but high
specificity for malaria diagnosis [53], while others excluded
malaria in their choice of diseases under examination [56]. A
more recent study in Tanzania with comparable endemicity to
western Kenya found the sensitivity, specificity, and positive
predictive value of malaria diagnosis among older children and
adults by VA to be 0.63, 0.90, and 0.70 compared with mortality
record death certificates [57]. While malaria is not recognised as a
major cause of death among older children in highly endemic
malarious areas in SSA [58], a study investigating malaria-
associated deaths globally from modelled VA, vital registration,
Table 5. Trends in non-communicable disease mortality rates per 100,000 by gender and age group.
Female MR
a
Male MR
a
RR
fem
(95% CI) x
2
P value M:F Ratio
15–24y 2003 141 128 1.10 (0.58–2.09) 0.09 0.76 0.91
2004 169 105 1.62 (0.85–3.08) 2.17 0.14 0.62
2005 56 82 0.68 (0.28–1.66) 0.73 0.39 1.46
2006 153 81 1.90 (0.94–3.83) 2.28 0.13 0.53
2007 109 132 0.83 (0.43–1.60) 0.31 0.58 1.21
2008 118 117 1.01 (0.53–1.95) 0.00 0.97 0.99
2009 95 140 0.68 (0.34–1.33) 1.29 0.26 1.47
x
2
LT
b
1.49 0.63 MHRR
c
1.07 (0.83–1.38); Summary x
2
0.21; p = 0.65
P value 0.22 0.43
15–19y 2003 58 76 0.76 (0.24–2.39) 0.2 0.64 1.31
2004 104 76 1.37 (0.51–3.68) 0.4 0.53 0.73
2005 47 74 0.63 (0.18–2.14) 0.6 0.45 1.57
2006 97 54 1.79 (0.59–5.48) 1.1 0.45 0.56
2007 60 118 0.50 (0.18–1.45) 1.7 0.19 1.97
2008 69 95 0.73 (0.26–2.05) 0.4 0.55 1.38
2009 72 131 0.55 (0.21–1.46) 1.5 0.22 1.82
x
2
LT
b
0.018 2.28 MHRR
c
0.81 (0.55–1.20); Summary x
2
0.9; 0.34
P value 0.93 0.13
20–24y 2003 272 225 1.21 (0.56–2.63) 0.2 0.64 0.83
2004 272 157 1.73 (0.73–4.07) 1.6 0.21 0.58
2005 71 97 0.73 (0.20–2.72) 0.2 0.75 1.37
2006 230 125 1.84 (0.74–4.55) 1.8 0.18 0.54
2007 176 154 1.15 (0.48–2.77) 0.1 0.76 0.88
2008 182 150 1.21 (0.51–2.87) 0.2 0.67 0.82
2009 126 155 0.81(0.31–2.10) 0.2 0.67 1.23
x
2
LT
b
1.83 0.11 MHRR
c
1.25 (0.89–1.74); Summary x
2
1.3; p = 0.239
P value 0.18 0.74
NOTE. RR
fem
, Relative risk for females compared with males; CI, confidence interval; x
2
, chi-squared.
a
MR, mortality rates per 100,000, includes deaths ascribed to injuries, CNS, nutritional, maternal, respiratory, gut, liver, cancers, cardio-vascular, renal/urinary, and
diabetes.
b
x
2
LT, chi-squared for linear trend.
c
MHRR, Mantel Haenszel weighted relative risk, and Greenlands-Robins 95% confidence intervals.
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and hospital data, has postulated that malaria deaths among adults
may have been under-diagnosed [59]. While malaria-related care
for pregnant women [52,60], and household level protection
against transmission [31], has been a focus of attention in the study
site, however, we found no significant change over time in
mortality rates of malaria-ascribed deaths. Misclassification may
also occur with co-infections other than malaria and TB, with duel
HIV infection driving mortality [61]. Studies in the area around
Lake Victoria have found compelling evidence of co-morbidity
with schistosomiasis [36], although schistosomiasis was not
recorded or attributed to any CD deaths among AYA during this
study period.
NCD mortality primarily represented traumatic injuries for
males; and ascription of cause through VA appears less
problematical [53]. Absence of diagnostic testing of NCD in
this rural setting likely contributed to potential domination of
trauma and under-representation of other NCD causes, with
attribution to other common causes. While trauma was reported
as a cause of death among females, and mortality rates rose
relative to other causes, the relatively limited number of deaths
ascribed is surprising and not consistent with a national survey
documenting that 35.8% of female respondents in western
Kenya reported inter-personal violence occurring during the
past 12 months [47].
Other NCD causes may be due to a CD; for example, of the
CNS deaths 91% were attributed to seizures/epilepsy. Persisting
neurological sequelae are recognised to be the long-term
consequence of cerebral malaria occurring during childhood
[62,63], thus, a proportion may have malaria as the originating
underlying cause in this area which has intense malaria
transmission. Neurological complications are also documented in
association with opportunistic infections among HIV infected
persons despite ART [64]; and HIV was found to be an
independent predictor of death among epileptic patients in
Ethiopia [65]. Other NCD, such as cardiac, respiratory and renal
disease may be falsely attributed to organ failure because of
incomplete recall of symptoms remembered by relatives. Exclud-
ing deaths from injury and from maternal causes, mortality
attributed to NCD contributed a very small proportion of deaths
among AYA in rural western Kenya; however, NCD is expected
to rise as westernised behaviours and wealth increases, as well as
access to diagnostic screening [8,15,66]. There remains, never-
theless, a clear need for refinement of VA to further improve
sensitivity and specificity of algorithms for both CD and NCD
[59,67]. Evaluation of cause in rural areas, through post-mortem
autopsy and biopsies, will contribute towards this and improve the
differential diagnoses of deaths. An INDEPTH funded pilot study
to evaluate this in our HDSS site is underway.
Conclusion
This study has identified a halving in the all-cause mortality rate
of adolescent and young adult females aged 15–24 years in rural
western Kenya over seven years. This runs in tandem with
substantive improvements in HIV treatment and care services.
While this provides evidence that targeted public health
programmes can have significant impact, all-cause and CD
mortality rates among females still remain alarmingly high,
underscoring the need to further strengthen programmes. The
absence of significant reductions among males highlights the need
to adapt and strengthen programmes and target strategies to reach
both males and females. Expanding and targeting preventive
health care services for the main contributors to NCD, such as
injuries and maternal health, are called for. Findings highlight the
necessity for new research to examine the validity of verbal
autopsy for ascribing cause of death in rural SSA.
Acknowledgments
The communities of Asembo and Gem are warmly thanked for their
enduring support of the HDSS, and assisting our staff with surveillance and
study activities. Field staff are thanked for their dedication and contribution
towards our public health endeavours. We acknowledge the contribution of
HDSS staff, data managers, and clerical assistants to this work. Rose Okolo
provided administrative support. The INDEPTH Network is thanked for
its on-going collaboration to strengthen and suppo rt health and
demographic surveillance systems: the KEMRI/CDC HDSS is a member
of the INDEPTH Network. We acknowledge Dr Kubaje Adazu as a co-
author. Originally from Ghana, he had been the Chief of the HDSS in
western Kenya since 2001, but died suddenly in January 2009. He made a
tremendous contribution to the development and implementation of the
KEMRI/CDC HDSS. The Director of KEMRI has approved this
manuscript.
Author Contributions
Conceived and designed the experiments: PPH KL. Analyzed the data:
PPH FO VO. Wrote the paper: PPH FO KL MH AvH AvE MA CB LS
RB. Provided scientific leadership: KdC RB JV LS KL. Reviewed the
manuscript: PPH FO KL MH AvH AvE MA CB LS RB MB KdC JV.
Commented on the manuscript: PPH FO KL MH AvH AvE MA CB LS
RB. Gave permission for data to be used and published: FO KL JV.
Conducted and/or supported the conduct of the field work: KA FO MH
AvH VO AvE LS RB KdC JV KL RB.
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Mortality in Adolescents and Young Adults
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    • "According to the report, tuberculosis remains among the top three killers of women [30]. In line with our findings, different studies have also reported the public health burden of tuberculosis and HIV/AIDS among female population in sub-Saharan African countries including Ethiopia [2,4,11,313233. These finds signal the need of more efforts to prevent tuberculosis related mortality among females. "
    [Show abstract] [Hide abstract] ABSTRACT: Background: In developing countries, investigating mortality levels and causes of death among all age female population despite the childhood and maternal related deaths is important to design appropriate and tailored interventions and to improve survival of female residents. Methods: Under Kilite-Awlealo Health and Demographic Surveillance System, we investigated mortality rates and causes of death in a cohort of female population from 1st of January 2010 to 31st of December 2012. At the baseline, 33,688 females were involved for the prospective follow-up study. Households under the study were updated every six months by fulltime surveillance data collectors to identify vital events, including deaths. Verbal Autopsy (VA) data were collected by separate trained data collectors for all identified deaths in the surveillance site. Trained physicians assigned underlining causes of death using the 10th edition of International Classification of Diseases (ICD). We assessed overall, age- and cause-specific mortality rates per 1000 person-years. Causes of death among all deceased females and by age groups were ranked based on cause specific mortality rates. Analysis was performed using Stata Version 11.1. Results: During the follow-up period, 105,793.9 person-years of observation were generated, and 398 female deaths were recorded. This gave an overall mortality rate of 3.76 (95% confidence interval (CI): 3.41, 4.15) per 1,000 person-years. The top three broad causes of death were infectious and parasitic diseases (1.40 deaths per 1000 person-years), non-communicable diseases (0.98 deaths per 1000 person-years) and external causes (0.36 per 1000 person-years). Most deaths among reproductive age female were caused by Human Deficiency Virus/Acquired Immune Deficiency Virus (HIV/AIDS) and tuberculosis (0.14 per 1000 person-years for each cause). Pregnancy and childbirth related causes were responsible for few deaths among women of reproductive age--3 out of 73 deaths (4.1%) or 5.34 deaths per 1,000 person-years. Conclusions: Communicable diseases are continued to be the leading causes of death among all age females. HIV/AIDS and tuberculosis were major causes of death among women of reproductive age. Together with existing efforts to prevent pregnancy and childbirth related deaths, public health and curative interventions on other causes, particularly on HIV/AIDS and tuberculosis, should be strengthened.
    Full-text · Article · Sep 2014
    • "The area typifies the disease burden of rural African communities [28]. Mortality among adolescents and young people is predominantly attributed to communicable diseases and injuries [35]. Nyanza Province also ranked highest amongst all provinces in Kenya on measures of physical and sexual violence against females, with 12% of women reporting their first sexual intercourse was against their will [36]. "
    [Show abstract] [Hide abstract] ABSTRACT: Keeping girls in school offers them protection against early marriage, teen pregnancy, and sexual harms, and enhances social and economic equity. Studies report menstruation exacerbates school-drop out and poor attendance, although evidence is sparse. This study qualitatively examines the menstrual experiences of young adolescent schoolgirls. The study was conducted in Siaya County in rural western Kenya. A sample of 120 girls aged 14-16 years took part in 11 focus group discussions, which were analysed thematically. The data gathered were supplemented by information from six FGDs with parents and community members. Emergent themes were: lack of preparation for menarche; maturation and sexual vulnerability; menstruation as an illness; secrecy, fear and shame of leaking; coping with inadequate alternatives; paying for pads with sex; and problems with menstrual hygiene. Girls were unprepared and demonstrated poor reproductive knowledge, but devised practical methods to cope with menstrual difficulties, often alone. Parental and school support of menstrual needs is limited, and information sparse or inaccurate. Girls' physical changes prompt boys and adults to target and brand girls as ripe for sexual activity including coercion and marriage. Girls admitted 'others' rather than themselves were absent from school during menstruation, due to physical symptoms or inadequate sanitary protection. They described difficulties engaging in class, due to fear of smelling and leakage, and subsequent teasing. Sanitary pads were valued but resource and time constraints result in prolonged use causing chafing. Improvised alternatives, including rags and grass, were prone to leak, caused soreness, and were perceived as harmful. Girls reported 'other girls' but not themselves participated in transactional sex to buy pads, and received pads from boyfriends. In the absence of parental and school support, girls cope, sometimes alone, with menarche in practical and sometimes hazardous ways. Emotional and physical support mechanisms need to be included within a package of measures to enable adolescent girls to reach their potential.
    Full-text · Article · Nov 2013
  • [Show abstract] [Hide abstract] ABSTRACT: Information on trauma-related deaths in low and middle income countries is limited but needed to target public health interventions. Data from a health and demographic surveillance system (HDSS) were examined to characterise such deaths in rural western Kenya. Verbal autopsy data were analysed. Of 11,147 adult deaths between 2003 and 2008, 447 (4%) were attributed to trauma; 71% of these were in males. Trauma contributed 17% of all deaths in males 15 to 24 years; on a population basis mortality rates were greatest in persons over 65 years. Intentional causes accounted for a higher proportion of male than female deaths (RR 2.04, 1.37-3.04) and a higher proportion of deaths of those aged 15 to 65 than older people. Main causes in males were assaults (n=79, 25%) and road traffic injuries (n=47, 15%); and falls for females (n=17, 13%). A significantly greater proportion of deaths from poisoning (RR 5.0, 2.7-9.4) and assault (RR 1.8, 1.2-2.6) occurred among regular consumers of alcohol than among non-regular drinkers. In multivariate analysis, males had a 4-fold higher risk of death from trauma than females (Adjusted Relative Risk; ARR 4.0; 95% CI 1.7-9.4); risk of a trauma death rose with age, with the elderly at 7-fold higher risk (ARR 7.3, 1.1-49.2). Absence of care was the strongest predictor of trauma death (ARR 12.2, 9.4-15.8). Trauma-related deaths were higher among regular alcohol drinkers (ARR 1.5, 1.1-1.9) compared with non-regular drinkers. While trauma accounts for a small proportion of deaths in this rural area with a high prevalence of HIV, TB and malaria, preventive interventions such as improved road safety, home safety strategies for the elderly, and curbing harmful use of alcohol, are available and could help diminish this burden. Improvements in systems to record underlying causes of death from trauma are required.
    Full-text · Article · Nov 2013
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