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RESEARCH ARTICLE
Global prevalence of preterm birth among
Pacific Islanders: A systematic review and
meta-analysis
Bohao WuID
1
, Veronika ShabanovaID
2,3
, Kendall ArslanianID
4
, Kate Nyhan
5,6
,
Elizabeth IzampuyeID
1
, Sarah Taylor
2
, Bethel Muasau-Howard
7
, Alec Ekeroma
8
, Nicola
L. HawleyID
1
*
1Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, United
States of America, 2Department of Pediatrics, Yale School of Medicine, New Haven, CT, United States of
America, 3Department of Biostatistics, Yale School of Medicine, New Haven, CT, United States of America,
4Department of Social and Behavioral Sciences, Yale School of Public Health, New Haven, CT, United
States of America, 5Harvey Cushing/John Hay Whitney Medical Library, Yale University, New Haven, CT,
United States of America, 6Department of Environmental Health Sciences, Yale School of Public Health,
Yale University, New Haven, CT, United States of America, 7Department of Obstetrics and Gynecology,
Lyndon B Johnson Tropical Medical Center, Pago Pago, American Samoa, 8National University of Samoa,
Apia, Samoa
*nicola.hawley@yale.edu
Abstract
The epidemiology of preterm birth among Pacific Islanders is minimally understood. The pur-
pose of this study was to estimate pooled prevalence of preterm birth among Pacific Island-
ers and to estimate their risk of preterm birth compared to White/European women. We
searched MEDLINE, EMBASE, Web of Science Core Collection, Cochrane Library, CINAHL,
Global Health, and two regional journals in March 2023. Observational studies were included
if they reported preterm birth-related outcomes among Pacific Islanders. Random-effects
models were used to estimate the pooled prevalence of preterm birth with 95% confidence
interval (CI). Bayes meta-analysis was conducted to estimate pooled odds ratios (OR) with
95% highest posterior density intervals (HPDI). The Joanna Briggs Institute checklists were
used for risk of bias assessment. We estimated preterm birth prevalence among Pacific
Islanders in the United States (US, 11.8%, sample size [SS] = 209,930, 95% CI 10.8%-
12.8%), the US-Affiliated Pacific Islands (USAPI, SS = 29,036, 6.7%, 95% CI 4.9%-9.0%),
New Zealand (SS = 252,162, 7.7%, 95% CI 7.1%-8.3%), Australia (SS = 20,225, 6.1%, 95%
CI 4.2%-8.7%), and Papua New Guinea (SS = 2,647, 7.0%, 95% CI 5.6%-8.8%). Pacific
Islanders resident in the US were more likely to experience preterm birth compared to White
women (OR = 1.45, 95% HPDI 1.32–1.58), but in New Zealand their risk was similar (OR =
1.00, 95% HPDI 0.83–1.16) to European women. Existing literature indicates that Pacific
Islanders in the US had a higher prevalence of preterm birth and experienced health inequi-
ties. Learning from New Zealand’s culturally-sensitive approach to health care provision may
provide a starting point for addressing disparities. The limited number of studies identified
may contribute to higher risk of bias and the heterogeneity in our estimates; more data is
needed to understand the true burden of preterm birth in the Pacific region.
PLOS GLOBAL PUBLIC HEALTH
PLOS Global Public Health | https://doi.org/10.1371/journal.pgph.0001000 June 14, 2023 1 / 19
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OPEN ACCESS
Citation: Wu B, Shabanova V, Arslanian K, Nyhan
K, Izampuye E, Taylor S, et al. (2023) Global
prevalence of preterm birth among Pacific
Islanders: A systematic review and meta-analysis.
PLOS Glob Public Health 3(6): e0001000. https://
doi.org/10.1371/journal.pgph.0001000
Editor: Hermano Alexandre Lima Rocha, Federal
University of Ceara, UNITED STATES
Received: August 8, 2022
Accepted: May 4, 2023
Published: June 14, 2023
Copyright: ©2023 Wu et al. This is an open access
article distributed under the terms of the Creative
Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in
any medium, provided the original author and
source are credited.
Data Availability Statement: All data can be found
in the manuscript and supporting information files.
Funding: This works was supported by the US
National Institute of Health (PI: Hawley, NLH, grant
number R03HD093993). The funders had no role
in the design, analysis or compiling this
manuscript.
Competing interests: The authors have declared
that no competing interests exist.
Introduction
In light of persistent disparities in perinatal health between minority and majority populations
globally, greater attention is being paid to understanding unique risks that explain minority
populations increased risk of preterm birth (live birth before 37 weeks gestation [1]). Despite
efforts over the past several decades to intervene, preterm birth remains the leading cause of
both neonatal and under five year death [2,3]. In 2014, which is the most recent estimate from
the World Health Organization, the global prevalence of preterm birth was 10.6% (uncertainty
interval 9.0%-12.0%) [4].
Pacific Islanders are particularly underrepresented in perinatal health research, and little is
known about the prevalence of preterm birth among this group. Data from the Pacific Islands
themselves is sparse, both as a result of geographic isolation (~1000 islands across 300,000
square miles [5]) and nascent research infrastructure. Pacific Islander migrants are, however,
among the fastest growing minority groups in the United States (US), New Zealand, and Aus-
tralia. In the US, 1.2 million people identified as Native Hawaiian or Other Pacific Islanders
(NHOPI) in 2010 [6]. In the 2018 census 24.6% of New Zealanders identified as Māori or
Pacific Islander [7], and in Australia (2016), ~250,000 people reported Pacific Islander ethnic-
ity [8]. While data from these settings should allow for ethnicity-specific examination of health
outcomes, Pacific Islanders continue to be aggregated with other minority groups; in the US
with Asian or Native Americans (or Pacific Islanders are omitted from analyses because of
small sample size), and in Australia with Indigenous Australian groups.
Health challenges common among Pacific Islanders, such as, disproportionately high prev-
alence of obesity and obesity-related complications [5], may put them at a higher risk of pre-
term birth [5,9]. Obesity is a significant risk factor for pre-eclampsia and pre-pregnancy
diabetes [10,11], which have been associated with indicated preterm births [12]. Endemic
tropical illnesses may also increase risk [12,13]: Papua New Guinea, for example, still has a
high rate of malaria [14]. Furthermore, Pacific Islander migrants in developed countries may
have limited access to social services [15–18] and reportedly experience discrimination [19],
which may worsen their perinatal health outcomes.
To better understand the epidemiology of preterm birth among Pacific Islanders and the
need for perinatal health intervention, this systematic review and meta-analysis aims to: (a)
estimate the pooled prevalence of preterm birth among Pacific Islanders globally; and (b) iden-
tify whether Pacific Islanders were more likely to experience preterm birth compared to non-
Hispanic White/European women.
Materials and methods
Protocol and registration
This review (PROSPERO ID: CRD42021283377, protocol [20]) followed Preferred Reporting
Items for Systematic Reviews and Meta Analyses (PRISMA) [21] and Meta-analysis of Obser-
vational Studies in Epidemiology (MOOSE) reporting guidelines [22] and received Institu-
tional Review Board exemption.
Study population
Studies reporting outcomes of Pacific Islanders, including Native Hawaiians, residents in
Micronesia, Melanesia, and Polynesia were eligible for inclusion. Countries/territories were
selected based on the Pacific Island Countries [23] and previous studies [5,15], including US-
affiliated Pacific Islands (USAPI: American Samoa, Guam, Commonwealth of the Northern
Mariana Islands [CNMI], Federated States of Micronesia, Republic of the Marshall Islands
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Preterm birth prevalence among Pacific Islanders: A meta-analysis
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[RMI], and Palau), Kiribati, Nauru, Papua New Guinea, Solomon Islands, Fiji, New Caledonia,
Vanuatu, Tonga, Tuvalu, Tokelau, Niue, French Polynesia, New Zealand (Māori, the indige-
nous Polynesian people of New Zealand), Samoa, and the Cook Islands. Studies from the US
(Hawai’i and the contiguous US) and Australia (individuals from Ni-Vanuatu, Tahiti, and the
Pitcairn islands; Aboriginal and Torre Strait Islanders were not included) were included, since
there are large migrant populations in both countries.
Information sources
We searched MEDLINE ALL (Ovid), EMBASE (Ovid), Web of Science Core Collection (as
licensed at Yale [20]), Cochrane Library, CINAHL (EBSCOhost), and Global Health. The
Pacific Journal of Reproductive Health and Pacific Health Dialog were searched manually
since they are not well indexed in major bibliographic databases. Backwards and forwards cita-
tion chaining was searched by hand via Google Scholar. Reports from international, national,
state-level, and territorial government agencies were searched manually.
Search strategy
The search strategy was developed by the first author in consultation with all co-authors,
including a medical librarian (KN). The search used two concepts: (1) Pacific Islanders and (2)
preterm birth outcomes. Appropriate controlled vocabulary terms and keyword search terms
were used (MEDLINE ALL example, S1 Table) and archived [24].
Study selection
Peer-reviewed observational studies and agency reports published before March 17
th
2023
were included. Case reports and case-control studies were excluded due to inability to estimate
prevalence. While doctoral theses were included, conference abstracts and master’s theses
were not since final study outcomes may not have been available/reported.
Using Covidence data management software, each article was screened by two authors
independently at the title-abstract and full-text screening stages. Authors met to reach consen-
sus on inclusion and reasons for exclusion. Screening questions are presented in S2 Table.
Studies using the same datasets with the same study period were examined for potential sample
overlap. Where overlap was identified, only the study with the largest sample size was retained
in analyses.
Data extraction
Data extraction was completed by the first author and checked by the senior author. Extracted
information included preterm birth-related outcomes (prevalence among Pacific Islander
women and non-Hispanic White/European women), data source, publication date, data col-
lection period, study country/setting, study design, gestational age (GA) measurement
method, Pacific Islander ethnicity, and sample size.
For the prevalence estimate, if a study reported prevalence but not the absolute number of
events, this number was calculated with N(Preterm Births) = P*N(total Pacific Islanders) and
rounded to the next whole number, where N represented sample size and P represented preva-
lence of preterm birth. To compare risk among Pacific Islander and White/European women,
the prevalence among the two groups and the modelling outcomes (odds radio [OR], model-
ling method, and adjusted confounders) were recorded. For studies reporting prevalence, OR
were calculated with OR = ad/bc.
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Preterm birth prevalence among Pacific Islanders: A meta-analysis
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Risk of bias assessment
The Joanna Briggs Institute (JBI) [25] checklist for prevalence studies [26] was used for the
assessment in prevalence meta-analyses; the checklist for cross-sectional studies [27] was used
for meta-analyses comparing risk. Two authors (BW and EI) completed appraisals and dis-
agreements were discussed to reach consensus. Total scores represented the proportion of
“checks” with 100% the maximum possible score. Egger’s test [28] (for prevalence meta-analy-
ses) and weight-function models [29] (for Bayesian risk comparison meta-analyses) were used
to assess publication bias.
Synthesis of results
Stratified by study country/territory, we conducted prevalence meta-analyses of preterm birth
among Pacific Islander women and comparison of preterm birth risk meta-analyses between
Pacific Islander women and non-Hispanic White women in the US and New Zealand. As ran-
dom-effects models (DerSimonian and Laird method) [30] consider the included studies to be
a representative sample of possible articles on the research question of interest, these models
were used for the pooled prevalence with 95% confidence intervals (CI). I
2
is usually high in
prevalence meta-analysis but may not indicate the data is inconsistent [31,32], and it can be
biased in small meta-analyses [33], so we reported tau with both the inverse variance (IV)
method (weighting more to studies with a larger sample size) and the generalized linear mixed
models (GLMM) method (weighting more to studies with smaller sample size) for the hetero-
geneity assessment. We compared the estimated tau
2
[IV] to the within-study variances, with
tau
2
[IV] larger than within-study variance indicating the weights of any two studies are
approximately equal [34]. A large proportion of equal weights in a meta-analysis indicates the
heterogeneity exists. Prediction intervals were presented in which future studies effects may
fall based on present evidence. Subgroup analyses by Pacific Islander ethnicity were conducted
to understand the between-study heterogeneity.
For the pooled risk comparison estimate, we used a Bayesian meta-analysis method [35] due to
the relatively small number of studies identified by our search. Pooled ORs with 95% highest pos-
terior density intervals (HPDI) were reported. We assumed no association, so we restricted the
effect ln(OR) to normal prior centered at ln(OR)
p
= 0 (no effect), and the prior standard deviation
was restricted to σ
p
= 4; the priori expected heterogeneity was restricted to tau �0.98 with 95%
probability as half-normal priori with scale 0.5. Tau with 95% HPDI were used for the heterogene-
ity assessment. Prediction intervals and subgroup analyses by ethnicity were also provided.
All analyses were performed using RStudio (RStudio, Inc., Boston, MA, USA). The R pack-
age meta [36] was used to conduct prevalence meta-analyses and to generate Forest plots and
package dmetar [37] was used to perform Egger’s test for the corresponding publication bias
assessment; package bayesmeta [38] was used to conduct Bayes meta-analyses, and package
RoBMA [39] was used to perform the corresponding publication bias assessment (Bayes factor
[BF]<3 indicating weak evidence[40]). R code is provided in S1 Appendix.
Results
Study selection
We identified 10,077 articles from six databases and 15 articles from gray literature on Decem-
ber 3
rd
2021, and updated our search (2nd search) in these six databases on March 17
th
2023
(Fig 1). After removing duplicates, title-abstract and full-text screening, and adding articles
through citation chaining, we found 118 articles reporting preterm birth-related outcomes
among Pacific Islanders among which 55 articles reported results related to our objectives.
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After removing studies with overlapping data (S3 Table), we included 33 articles that reported
preterm birth prevalence, and 15 articles that compared risk between Pacific Islander and
White/European women.
Study characteristics
Of the 33 studies that reported prevalence of preterm birth among Pacific Islander women, 13
(39.4%) studies [41–53] were conducted in the US, 5 (15.2%) studies were conducted in the
Fig 1. PRISMA flow diagram of study selection.
https://doi.org/10.1371/journal.pgph.0001000.g001
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Preterm birth prevalence among Pacific Islanders: A meta-analysis
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USAPI [54–58] (CNMI [57,58], Palau [56], and RMI [54,55]), 7 (21.2%) studies were from
New Zealand [59–65], 2 (6.1%) studies were from Australia [66,67], 4 (12.1%) studies [68–71]
reported preterm birth prevalence in Papua New Guinea, 1 study was from Solomon Island
[72], and 1 study was from Vanuatu [73] (Table 1). Of the 15 studies used for the risk compari-
son meta-analysis, 12 (80.0%) [41–48,50,53,74,75] were conducted in the US, and 3 (20.0%)
were from New Zealand [76–78].
Almost half of the 41 total included studies [41,44,47,49,51–55,61–63,65–67,70,72,73,
77,79,80] (43.9%) did not report the method used to estimate GA. Seven (17.1%) studies used
last menstrual period (LMP) only [45,47,48,56,60,78,79] and seven (17.1%) used clinical/
obstetric estimates [43,46,50,57,59,74,81]. In two (4.9%) studies [58,64], GA was deter-
mined by the obstetric care provider at birth; two (4.9%) studies used ultrasound [68,76] and
one used Dubowitz assessment [69] (2.4%). The remaining three studies [42,71,75] (7.3%)
used a combination of ultrasound, LMP, and/or clinical estimate. Most included studies
defined preterm birth as occurring before 37 weeks, four (9.8%) [41,54,63,73] did not report
their GA threshold, two [58,62] (4.9%) used <36 weeks, and one [68] (2.4%) used <38 weeks.
Risk of bias
For the prevalence meta-analysis, risk of bias scores ranged from 55.6% to 100.0%, with higher
scores indicating lower risk of bias (S4 and S5 Tables). For the meta-analysis comparing risk,
risk of bias scores ranged from 37.5% to 100.0%; confounders included in models and model-
ling methods were summarized for each study in S6 Table.
Synthesis of results
Prevalence of preterm birth. In the US, the random-effects pooled prevalence of preterm
birth among Pacific Islanders was 11.8% (95% CI 10.8%-12.8%; tau [IV] = 0.17, 95% CI 0.16–
0.41; tau [GLMM] = 0.27), and the prediction interval ranged from 8.3% to 16.4% (Fig 2A). In
subgroup analysis, the random-effects pooled prevalence of preterm birth among Marshallese
(20.5%, 95% CI 17.7%-23.7%, tau[IV] = 0.12, tau[GLMM] = 0.06) was twice the pooled preva-
lence among the general Pacific Islander population in the US, and almost the same for other
ethnicities (S1 Fig). The pooled prevalence was lower in the USAPI (6.7%, 95% CI 4.9%-9.0%,
tau[IV] = 0.36, 95% CI 0.22–1.10; tau[GLMM] = 0.34), but the prevalence interval ranged
from 2.0% to 20.4% (Fig 2B).
The random-effects pooled prevalence of preterm birth among Pacific Islanders overlapped
in New Zealand, Australia, and Papua New Guinea (Fig 2C–2E). In New Zealand, the pooled
prevalence was 7.7% (95% CI 7.1%-8.3%, tau[IV] = 0.09, 95% CI 0.06–0.36; tau[GLMM] =
0.08) and the prediction interval ranged from 6.0% to 9.7%. In subgroup analysis (S2 Fig), we
found no obvious difference between the prevalence among Māori (8.4%, 95% CI 7.1%-9.8%)
and other Pacific Islanders (7.5%, 95% CI 6.8%-8.3%). In Australia, the pooled prevalence was
6.1% (95% CI 4.2%-8.7%, tau[IV] = 0.27; tau[GLMM] = 0.19). The pooled prevalence of pre-
term birth in Papua New Guinea was 7.0% (95% CI 5.6%-8.8%, tau[IV] = 0.17, 95% CI 0–1.05;
tau[GLMM] = 0.12), and the prediction interval ranged from 2.9% to 15.9%.
Comparison of preterm birth risk between Pacific Islander and White/
European women
Based on 12 studies from the US, we estimated the pooled odds of preterm birth among Pacific
Islander women to be 46% higher than among non-Hispanic White women (OR = 1.45, 95%
HPDI 1.32–1.58, tau = 0.16, 95% HPDI 0.11–0.24 (Fig 3A). In subgroup analysis, Hawaiian
(OR = 1.34, 95% HPDI 1.21–1.44, tau = 0.04, 95% HPDI 0.00–0.17), Marshallese (OR = 1.72,
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Preterm birth prevalence among Pacific Islanders: A meta-analysis
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Table 1. Characteristics of included studies for preterm birth among Pacific Islanders.
Study Data
collection
Study design State/Setting, Dataset Pacific Islanders GA measurement
method
PTB
definition
US (N = 18:13 were used for prevalence estimate; 12 were used for risk comparison)
Crowell et al., 2007 [47]
a, b, c, d
1968–1994 Retrospective
cohort study
e
Hawaii State,
birth record files
Hawaiian (n = 69,350)
Samoan (n = 7,054)
White (n = 108,981)
LMP GA <37
weeks
Andrasfay et al., 2021
[48]
a, b
(G2 cohort)
1978–1995 Retrospective
cohort study
e
California,
California birth records
Hawaiian/Pacific Islander
(n = 1,577); White
(n = 185,949)
LMP GA <37
weeks
Korinek et al., 2021 [44]
a, b
1989–2015 Retrospective
cohort study
e
State of Utah,
Utah Population Database
NHOPI (n = 10,438)
White (n = 1,177,278)
Not reported GA <37
weeks
Nembhard et al., 2019
[42]
a, b, c, d
1997–2013 Cross-sectional
study
Arkansas,
Vital record files
Marshallese (n = 2,488,
missing value 270)
Non-Hispanic White
(n = 65,800)
Ultrasound (74%) GA <37
weeks
Mathews et al., 2003 [79]
c
2001 Cross-sectional
study
e
US continent,
National Vital Statistics Reports
Hawaiian (n = 6,411)
White (n = 3,177,698)
LMP GA <37
weeks
Hirai et al., 2013 [45]
a, b,
c, d
2002–2009 Cross-sectional
study
e
Hawaii,
Linked Infant Death Cohort Files
Native Hawaiian (n = 40,917)
White (n = 33,683)
LMP GA <37
weeks
Centers for Disease
Control and Prevention
et al., 2011 [52]
a
2003–2008 Descriptive
study
e
Washington State, King County,
US government census
Hawaiians/Pacific Islanders
(n = 2,200)
Not reported GA <37
weeks
Wong et al., 2008 [80]
c
2003 Retrospective
cohort study
US continent,
National Natality Files
Samoan (n = 1,835)
Guamanian (n = 30,353)
Hawaiian (n = 1,302)
Not reported GA <37
weeks
Schempf et al., 2010 [75]
b, c, d
2003–2005 Cross-sectional
study
e
California and Hawaii,
birth certificates
Native Hawaiian (n = 16,805)
Guamanian (n = 1,406)
Marshallese (n = 938)
Samoan (n = 4,820)
Tongan (n = 1,594)
White (n = 10,144)
CA: LMP;
HA: clinical estimate
GA <37
weeks
Altman et al., 2019 [49]
a,
c
2007–2012 Retrospective
cohort study
California,
birth records
Hawaiian (n = 756)
Guamanian (n = 844)
Samoan (n = 2,852)
Other Pacific Islander
(n = 5,422)
More than one (n = 596)
Not reported GA <37
weeks
Ratnasiri et al., 2018 [74]
b
2007–2016 Retrospective
cohort study
California,
Birth Statistical Master Files
N for races was not reported Obstetric estimate GA <37
weeks
Wartko et al., 2017 [41]
a,
b
2008–2012 Retrospective
cohort study
Washington State, King County,
birth records
NHOPI (n = 1,853)
White (n = 62,950)
Not reported Not reported
Hawaii State Department
of Health et al., 2019 [50]
a, b, d
2012–2015 Descriptive
study
e
Hawaii,
Pregnancy Risk Assessment
Monitoring System
Native Hawaiian (n = 5,050)
Samoan (n = 300)
Other Pacific Islander
(n = 950)
White (n = 4,400)
Clinical estimate GA <37
weeks
Public Health
Department, Seattle &
King County et al., 2015
[51]
a
2013 Descriptive
study
e
Washington State, King County,
birth certificate data
Pacific Islander (n not
reported)
White (n = 13,061)
Not reported GA <37
weeks
Quan et al., 2021 [81]
c
2015–2017 Cross-sectional
study
e
National Natality File NHOPI (n = 9,476) Obstetric estimate GA <37
weeks
Martin et al., 2019 [43]
a,
b
2016–2018 Descriptive
study
e
US continent,
Natality Data Files
NHOPI (n = 28,244)
White (n = 6,005,206)
Obstetric estimate GA <37
weeks
Hamilton et al., 2021
[46]
a, b
2019–2020 Descriptive
study
e
US continent,
Natality Data Files
NHOPI (n = 19,382)
White (n = 3,755,477)
Obstetric estimate GA <37
weeks
(Continued)
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Table 1. (Continued )
Study Data
collection
Study design State/Setting, Dataset Pacific Islanders GA measurement
method
PTB
definition
Hamilton et al., 2022
[53]
a, b
2021 Descriptive
study
e
US continent,
Natality Data Files
NHOPI (n = 9,517)
White (n = 1,884,554)
Obstetric estimate GA <37
weeks
USAPI (N = 5)
Fox et al., 2005 [58]
a
1986–1996 Retrospective
cohort study
e
Commonwealth of the Northern
Mariana Islands,
hospital records
Women from
Commonwealth of the
Northern Mariana Islands
(n = 10,756)
Determined by the
birth attendant
GA <36
weeks
Dela Cruz et al., 2018
[57]
a
2007–2014 Retrospective
cohort study
Commonwealth of the Northern
Mariana Islands,
hospital records
Chamorro/Carolinian
(n = 2,799)
Other Pacific Islander
(n = 785)
Obstetric estimate GA <37
weeks
Berger et al., 2016 [56]
a
2007–2013 Retrospective
cohort study
Palau,
hospital records
Palauan (n = 1,171) LMP GA <37
weeks
Ministry of Health in
Republic of the Marshall
Islands, 2010 [55]
a
2007–2010 Descriptive
study
e
Republic of the Marshall Islands,
Vital Statistics Database
Women from Republic of the
Marshall Islands (n = 6,116)
Not reported Not reported
Ministry of Health in
Republic of the Marshall
Islands, 2016 [54]
a
2011–2016 Descriptive
study
e
Republic of the Marshall Islands,
Vital Statistics Database
Women from Republic of the
Marshall Islands (n = 7,515)
Not reported GA <37
weeks
New Zealand (N = 10:7 were used for prevalence estimate; 3 were used for risk comparison)
Cantwell et al., 1973 [63]
a, c
Not
reported
Prospective
cohort study
Hawkes Bay,
hospital records
Maori (n = 276, missing value
n = 21)
Not reported Not reported
Wright et al., 1998 [59]
a,
c
1987–1990 Cross-sectional
study
Cot Death Study Maori (n = 306)
Pacific Islander (n = 154)
Clinical estimate GA <37
weeks
Sadler et al., 2002 [61]
a, c
1992–1999 Retrospective
cohort study
e
Auckland,
hospital records
Maori (n = 4,361)
Pacific Islander (n = 8,197)
Not reported GA <37
weeks
Lawton et al., 2016 [62]
a,
c
1995–2009 Retrospective
cohort study
Wellington region,
hospital records
Maori (n = 6,960)
Pacific Islander (n = 5,697)
European (n = 33,386)
Not reported GA <36
weeks
Craig et al., 2004 [76]
b, d
1996–2001 Retrospective
cohort study
e
Data file from New Zealand
Health Information Service
Maori (n = 72,826, missing
value 6,729, 9.2%)
Pacific Islander (n = 32,713,
missing value 3,515, 10.7%)
European (n = 192,295,
missing value 18,042, 9.4%)
Ultrasound GA <37
weeks
Sundborn et al., 2011
[60]
a, c
2000 Cross-sectional
study
e
South Auckland,
Pacific Island Families Study
Samoan (n = 627)
Cook Island Maori (n = 230)
Niuean (n = 57)
Tongan (n = 278)
LMP GA <37
weeks
Berry et al., 2018 [64]
a, c
2005–2015 Retrospective
cohort study
The Department of Internal
Affairs and the Ministry of
Health’s National Minimum
Dataset
Maori (n = 129,300)
Pacific Islander (n = 72,435)
Ascertained by the
obstetric care provider
GA <37
weeks
Parry et al., 2011 [78]
b, d
2007–2010 Prospective
cohort study
Auckland,
hospital records
Maori (n = 13,647)
Pacific peoples (n = 6,625)
European (n = 33,957)
LMP GA <37
weeks
Edmonds et al., 2021
[77]
b, d
2010–2014 Retrospective
cohort study
Kaupapa Maori research Maori (n = 77,601)
Pasifika (n = 33,106)
European (n = 141,815)
Not reported GA <37
weeks
Ministry of Health et al.,
2019 [65]
a
2016 Descriptive
study
e
New Zealand Mortality
Collection
Maori (n = 17,329)
Pacific peoples (n = 5,976)
Not reported GA <37
weeks
Australia (N = 2)
(Continued)
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Preterm birth prevalence among Pacific Islanders: A meta-analysis
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95% HPDI 1.07–2.33, tau = 0.27, 95% HPDI 0–0.72), and Samoan (OR = 1.36, 95% HPDI
0.93–1.74, tau = 0.22, 95% HPDI 0.04–0.58) women were all more likely to experience preterm
birth compared to non-Hispanic White women in the US (S3 Fig).
Using data from three studies from New Zealand we determined that the pooled odds of
preterm birth were similar for Pacific Islander and European women (OR = 1.00, 95% HPDI
0.83–1.16, tau = 0.16, 95% HPDI 0.07–0.34, Fig 3B). Stratified by ethnicity subgroups, neither
Māori (OR = 1.10, 95% HPDI 0.77–1.41, tau = 0.16, 95% HPDI 0.03–0.54) nor other Pacific
Islanders (OR = 0.90, 95% HPDI 0.61–1.18, tau = 0.14, 95% HPDI 0.02–0.50) had higher odds
of preterm birth compared to European women.
Heterogeneity assessment
Checking the proportion of the studies with a smaller variance than the tau
2
[IV] suggests that
no heterogeneity existed in the prevalence meta-analysis in the US (0%) and New Zealand
(0%), however, meta-analyses conducted for the USAPI (100.0%), Australia (100.0%) and
Papua New Guinea (100.0%) all showed strong evidence of heterogeneity. When using the
same method to check the proportion of the studies with a smaller variance of log scale of the
ORs (Varlog[OR]) than the tau
2
[IV] there was strong evidence of heterogeneity in meta-
Table 1. (Continued )
Study Data
collection
Study design State/Setting, Dataset Pacific Islanders GA measurement
method
PTB
definition
Berman et al., 2021 [67]
a
2003–2016 Retrospective
cohort study
Linked birth, hospital and death
data from New South Wales
Oceania (n = 17,284) Not reported GA <37
weeks
(Included 32–
36 weeks
only)
Mozooni et al., 2018 [66]
a
2005–2013 Retrospective
cohort study
Dataset from Western Australia
Data Linkage System
Maori (n = 2,941) Not reported GA <37
weeks
Papua New Guinea (N = 4)
Garner et al., 1994 [69]
a
1984–1987 Cross-sectional
study
e
Wosera subdistrict,
hospital records
Women from Papua New
Guinea (n = 121)
Dubowitz assessment GA <37
weeks
Allen et al., 1998 [68]
a
1994–1996 Prospective
cohort study
Madang Province,
hospital records
Women from Papua New
Guinea (n = 987)
Ultrasound GA <38
weeks
Senn et al., 2009 [70]
a
2007–2008 Cross-sectional
study
Madang Province,
hospital records
Women from Papua New
Guinea (n = 310)
Not reported GA <37
weeks
Unger et al., 2019 [71]
a
2009–2013 Prospective
cohort study
Madang Province,
hospital records
Women from Papua New
Guinea (n = 1,229)
Ultrasound (65.5%);
fetal biometry for the
majority
GA <37
weeks
Other Pacific Island countries (N = 2)
Cafaro et al., 2015 [72]
f
2011–2013 Retrospective
cohort study
Records from KiraKira Hospital,
Makira-Ulawa Province,
Solomon Island
Solomon Islander (n = 1,233) Not reported GA<37 weeks
Therrien et al., 2021 [73]
f
2016 Cross-sectional
study
e
Records from Vila Central
Hospital on Efate Island,
Vanuatu.
Women from Vanuatu
(n = 187)
Not reported Not reported
GA, gestational age; LMP, last menstrual period; NHOPI, Native Hawaiian and Other Pacific Islanders; CA, California; HA, Hawaii
a
Labelled studies were included in preterm birth prevalence meta-analyses.
b
Labelled studies were included in the risk of preterm birth compared to White/European women meta-analysis.
c
Labelled studies were included in preterm birth prevalence subgroup meta-analysis.
d
Labelled studies were included in the risk of preterm birth compared to White/European women subgroup meta-analyses.
e
The study design was not reported and was decide by the first author’s judgement.
f
Labelled studies were not included in meat-analyses since there was only one study from each setting.
https://doi.org/10.1371/journal.pgph.0001000.t001
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Preterm birth prevalence among Pacific Islanders: A meta-analysis
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analyses comparing risk between Pacific Islander and White/European women in the US
(95.2%) and New Zealand (100.0%).
Publication bias assessment
For preterm birth prevalence meta-analyses, we did not identify any publication bias (Egger’s
test, US: P = 0.54, USAPI: P = 0.35, New Zealand: P = 0.53, Papua New Guinea: P = 0.27). This
Fig 2. Forest plots of preterm birth prevalence among Pacific Islanders stratified by country/territory: (A) the US, (B) the
USAPI, (C) New Zealand, (D) Australia, (E) Papua New Guinea
a
.
a
Prediction interval of Australia is not available.
https://doi.org/10.1371/journal.pgph.0001000.g002
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Preterm birth prevalence among Pacific Islanders: A meta-analysis
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assessment was not available for Australia since Egger’s test cannot be used with <3 studies.
For the risk comparison meta-analyses, the robust Bayesian model expressed weak evidence of
publication bias in the US (probability = 0.42, inclusion BF = 0.73) and New Zealand (proba-
bility = 0.48, inclusion BF = 0.93).
Discussion
Main findings
To our knowledge, this is the first systematic review and meta-analysis to summarize data
from both Pacific Islander immigrants in high income settings and those resident in the Pacific
Islands. Results indicate that US-resident Pacific Islanders had a relatively higher prevalence of
preterm birth than in New Zealand and Australia and experienced poorer birth outcomes than
White women, which was an inequity not observed in New Zealand. Estimates in other set-
tings were limited by sparse data.
Our Pacific Islander-specific findings mirror the most recent country level estimates
reported by the WHO. In 2014, among the three developed nations, the US had the highest
overall preterm birth prevalence (9.6%, uncertainty interval [UI] 10.3%-14.0%), while the
Fig 3. Forest plots of risk of preterm birth comparing Pacific Islander women to (A) non-Hispanic White women in the US and to (B) European women in
New Zealand.
https://doi.org/10.1371/journal.pgph.0001000.g003
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Preterm birth prevalence among Pacific Islanders: A meta-analysis
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estimates in New Zealand (7.5%, UI 7.0%-9.8%) and Australia (8.6%, UI 6.9%-9.5%) were sim-
ilar [82]. Notably, in our analysis we identified disparities between Pacific Islander and white
women that were present in the US, but not in New Zealand. In New Zealand, while Pacific
Islanders have become a minority group since European occupation, they make up a far
greater proportion (24.6% [7]) of the population than in the US (0.4%) [83]. As such, support-
ive and culturally-based health policies have been prioritized in New Zealand to care for popu-
lations with high need (including Māori and Pacific Islanders) [84], such as Very Low Cost
Access (VLCA), Te Tiriti o Waitangi (the Treaty of Waitangi) [85], which protects Māori
resources, and iwi (tribally)-based primary care consistent with Māori values, attitudes, and
aspirations [86,87]. In contrast, in the US Pacific Islander women have reported limited health
care access related to citizenship [16,17], discrimination [19], and mistrust of health profes-
sionals [15–18]. Replicating New Zealand’s focus on primary health care, support for cultur-
ally-sensitive initiatives, and efforts to decrease structural racism [87–89] may be important if
US disparities are to be addressed.
While Australia has among the largest absolute number of Pacific Islander migrants, they
make up a small proportion (0.9%) of the population
12
, which likely explains the limited num-
ber of Pacific Islander-related studies reporting preterm birth. Australia has continuously sup-
ported seven surrounding Pacific Island countries to promote universal health coverage since
1995, including Fiji, Kiribati, Nauru, Samoa, Solomon Islands, Tonga and Vanuatu [90], but
did not systematically record maternal ethnicity other than Caucasian and Indigenous
(Aboriginal and Torres Strait Islander) in their own health system before 1998 [91]. Studies
indicate that language barriers and inadequate health care access may increase the burden of
adverse pregnancy outcomes among Pacific Islander migrants to Australia [66], but further
data, with improved specificity in race/ethnicity reporting, is needed to better understand
their perinatal outcomes.
Data from the Pacific Islands themselves were sparse and limited conclusions about the
prevalence of preterm birth. While Pacific Islander women in the USAPI had a lower preterm
birth estimate than the US, the wider prediction interval should be noted. All of the USAPIs
are medically underserved [92] and, although prenatal/obstetric care is available [93,94], cov-
erage in different settings varies [94,95] limiting opportunities for systematic data collection.
Further data is sorely needed to adequately understand the needs of these territories, which are
heavily dependent on US grant funding to sustain their health care systems.
Although Papua New Guinea is the largest of the Pacific Islands, with 8.9 million residents
[96], studies were limited by design and response rate. For several reasons, the estimated prev-
alence may not accurately reflect the national burden of preterm birth. First, most of the
included studies were from Madang Province, where much research is concentrated since the
province is home to one of the country’s two medical schools and the Papua New Guinea Insti-
tute of Medical Research. The relatively higher prenatal care coverage (63%) in this setting [97,
98] compared to other regions may reduce maternal morbidity during or after pregnancy,
meaning that estimates for preterm birth prevalence may be lower than the whole nation. Sec-
ond, although malaria—a known risk factor for preterm birth—is endemic to Papua New
Guinea (86% of cases in WHO Western Pacific Region were from Papua New Guinea [14]),
most women in the included studies had either taken malaria prophylaxis before the recruit-
ment or were cured before giving birth [68,69,71] (one study did not report malaria related
information [70]). This also may not be the case for women residing in more rural and less
medically served settings. Finally, in one of the largest samples of women among the Papua
New Guinea studies [68], preterm birth was defined as less than 38 weeks, which may also
have influenced the estimate.
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Preterm birth prevalence among Pacific Islanders: A meta-analysis
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Strengths and Limitations
Limitations of our study should be noted. Beyond the USAPIs, Papua New Guinea and New
Zealand there was little data on perinatal health from the remaining Pacific Islands. We identi-
fied only one study from Vanuatu [73] (PTB prevalence: 8.0%), and one study from the Solo-
mon Islands in which the reported preterm birth prevalence was 23.8% in 2011–2013 [72]
indicating that there may be broad heterogeneity in preterm birth prevalence across the region
that was not captured here. Even within our studies, a large degree of heterogeneity was evi-
dent in prevalence meta-analyses for the USAPI, Australia, and Papua New Guinea. Potential
explanations could include the lack of consistency in GA measurement methods, the limited
publications, and quality of health care provided by local clinics. Similar heterogeneity in the
risk comparison meta-analysis in the US may be from different perinatal outcomes among
Pacific Islander subgroups, particularly the much higher risk and prevalence of preterm birth
among Marshallese women; in New Zealand, the heterogeneity may be from different study
designs, varied GA measurement methods (most were unclear), and the unavoidable heteroge-
neity for smaller meta-analyses [33]. The large proportion of included studies that did not
clearly state the methods used to estimated GA also should be noted.
Our study does, however, have several notable strengths. We systematically searched arti-
cles reporting preterm birth outcomes among Pacific Islanders, including grey literature and
comprehensively conducted backward and forward citation chaining. Second, we used tau for
the heterogeneity assessment instead of I
2
statistics, which have been questioned for their reli-
ability especially for prevalence meta-analysis [31] and meta-analyses with a small number of
included studies [33]. Additionally, to increase the accuracy of our risk comparison estimates,
we used a Bayesian meta-analysis approach that performs better than frequentist meta-analysis
approach when a small number of studies are included [35], and the corresponding robust
Bayesian modelling method for publication bias assessment.
Interpretation
Our findings have important public health implications. In developed nations like the US and
Australia, an improved record of race/ethnicity information and ethnicity-specific analyses are
the first steps to understanding the burden of adverse pregnancy outcomes among minority
groups. It is vital to identify related, contextually relevant risk factors to inform future polices
to decrease health disparities. Lessons may be learned from New Zealand’s culturally-sensitive
approach. In the USAPI, Papua New Guinea, and the other Pacific nations not represented
here, basic health care infrastructure improvements are likely needed before the true burden of
preterm birth can be understood.
Conclusion
Existing literature indicates that Pacific Islanders in the US had a higher prevalence of preterm
birth than in other global settings and experienced health inequities. Learning from New Zeal-
and’s culturally-sensitive approach to health care provision may provide a starting point for
addressing disparities. Data from other Pacific settings is sparse, limiting conclusions about
prevalence. More data is needed to understand the true burden of preterm birth in the Pacific
region.
Supporting information
S1 Checklist. PRISMA 2020 checklist.
(DOCX)
PLOS GLOBAL PUBLIC HEALTH
Preterm birth prevalence among Pacific Islanders: A meta-analysis
PLOS Global Public Health | https://doi.org/10.1371/journal.pgph.0001000 June 14, 2023 13 / 19
S1 Table. Search strategy for systematic review of the literature on MEDLINE ALL (Ovid).
(DOCX)
S2 Table. Screening questions.
(DOCX)
S3 Table. Articles excluded due to overlapping data (n = 31).
(DOCX)
S4 Table. Risk of bias assessment for the preterm birth prevalence meta-analysis using the
JBI checklist [26].
(DOCX)
S5 Table. Risk of bias assessment for the risk comparison of preterm birth meta-analysis
using the JBI checklist [27].
(DOCX)
S6 Table. Summary for adjustment methods and confounding factors (risk comparison of
preterm birth meta-analysis).
(DOCX)
S1 Fig. Forest plot of preterm birth prevalence subgroup analysis by Pacific Islander eth-
nicity in the US
a a
Please note, the overall estimate presented here is not expected to match
that in Fig 2A since these analyses are restricted to only a sub-sample of the overall study
population.
(TIF)
S2 Fig. Forest plot of preterm birth prevalence subgroup analysis by Pacific Islander eth-
nicity in the New Zealand
a a
Please note, the overall estimate presented here is not expected
to match that in Fig 2C since these analyses are restricted to only a sub-sample of the over-
all study population.
(TIF)
S3 Fig. Forest plot of risk of preterm birth comparing Pacific Islander women to non-His-
panic White women subgroup by ethnicity in the US.
(TIF)
S1 Appendix. R code for meta-analyses.
(DOCX)
Author Contributions
Conceptualization: Bohao Wu, Veronika Shabanova, Sarah Taylor, Nicola L. Hawley.
Data curation: Bohao Wu, Nicola L. Hawley.
Formal analysis: Bohao Wu, Veronika Shabanova, Elizabeth Izampuye.
Funding acquisition: Nicola L. Hawley.
Investigation: Bohao Wu, Veronika Shabanova, Kate Nyhan, Sarah Taylor, Nicola L. Hawley.
Methodology: Bohao Wu, Veronika Shabanova, Kate Nyhan, Nicola L. Hawley.
Project administration: Bohao Wu, Kendall Arslanian, Kate Nyhan, Nicola L. Hawley.
Resources: Bohao Wu, Kendall Arslanian, Kate Nyhan, Elizabeth Izampuye, Nicola L. Hawley.
Software: Bohao Wu, Veronika Shabanova, Kate Nyhan, Nicola L. Hawley.
PLOS GLOBAL PUBLIC HEALTH
Preterm birth prevalence among Pacific Islanders: A meta-analysis
PLOS Global Public Health | https://doi.org/10.1371/journal.pgph.0001000 June 14, 2023 14 / 19
Supervision: Bohao Wu, Veronika Shabanova, Sarah Taylor, Nicola L. Hawley.
Validation: Bohao Wu, Veronika Shabanova, Sarah Taylor, Bethel Muasau-Howard, Alec
Ekeroma, Nicola L. Hawley.
Visualization: Bohao Wu, Veronika Shabanova.
Writing – original draft: Bohao Wu.
Writing – review & editing: Bohao Wu, Veronika Shabanova, Kendall Arslanian, Kate
Nyhan, Elizabeth Izampuye, Sarah Taylor, Bethel Muasau-Howard, Alec Ekeroma, Nicola
L. Hawley.
References
1. World Health Organization. Preterm birth 2018 [cited 2020 Sept]. Available from: https://www.who.int/
en/news-room/fact-sheets/detail/preterm-birth.
2. Lawn JE, Kinney M. Preterm birth: now the leading cause of child death worldwide. Sci Transl Med.
2014; 6(263):263ed221. https://doi.org/10.1126/scitranslmed.aaa2563 PMID: 25411468
3. McClure EM, Goldenberg RL, Jobe AH, Miodovnik M, Koso-Thomas M, Buekens P, et al. Reducing
neonatal mortality associated with preterm birth: gaps in knowledge of the impact of antenatal cortico-
steroids on preterm birth outcomes in low-middle income countries. Reprod Health. 2016; 13(1):1–4.
https://doi.org/10.1186/s12978-016-0180-6 PMID: 27221397
4. Chawanpaiboon S, Vogel JP, Moller A-B, Lumbiganon P, Petzold M, Hogan D, et al. Global, regional,
and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis.
Lancet Glob Health. 2019; 7(1):e37–e46. https://doi.org/10.1016/S2214-109X(18)30451-0 PMID:
30389451
5. Hawley NL, McGarvey ST. Obesity and diabetes in Pacific Islanders: the current burden and the need
for urgent action. Curr Diab Rep. 2015; 15(5):29. https://doi.org/10.1007/s11892-015-0594-5 PMID:
25809458
6. Lindsay Hixson BBH, kim Myoung Ouk. The Native Hawaiian and Other Pacific Islander Population:
2010: U.S. Department of Commerce, Economics and Statistics Administration, U.S. Census Bureau;
2012 [cited 2020 October 7]. Available from: https://www.census.gov/prod/cen2010/briefs/c2010br-12.
pdf.
7. New Zealand Government. 2018 census ethnic group summaries [cited 2022 February 12]. Available
from: https://www.stats.govt.nz/tools/2018-census-ethnic-group-summaries/m%C4%81ori.
8. Batley J. What does the 2016 census reveal about Pacific Islands communities in Australia? 2017 [cited
2020 Nov]. Available from: https://devpolicy.org/2016-census-reveal-about-pacific-islands-
communities-in-australia-20170928/.
9. Hawley NL, Johnson W, Hart CN, Triche EW, Ching JA, Muasau-Howard B, et al. Gestational weight
gain among American Samoan women and its impact on delivery and infant outcomes. BMC Pregnancy
Childbirth. 2015; 15(1):1–7. https://doi.org/10.1186/s12884-015-0451-1 PMID: 25643752
10. McDonald SD, Han Z, Mulla S, Beyene J. Overweight and obesity in mothers and risk of preterm birth
and low birth weight infants: systematic review and meta-analyses. Br Med J. 2010;341. https://doi.org/
10.1136/bmj.c3428 PMID: 20647282
11. Doherty DA, Magann E, Francis J, Morrison J, Newnham J. Pre-pregnancy body mass index and preg-
nancy outcomes. Int J Gynaecol Obstet. 2006; 95(3):242–247. https://doi.org/10.1016/j.ijgo.2006.06.
021 PMID: 17007857
12. Goldenberg RL, Culhane JF, Iams JD, Romero R. Epidemiology and causes of preterm birth. Lancet.
2008; 371(9606):75–84. https://doi.org/10.1016/S0140-6736(08)60074-4 PMID: 18177778
13. Rogerson SJ, Desai M, Mayor A, Sicuri E, Taylor SM, van Eijk AM. Burden, pathology, and costs of
malaria in pregnancy: new developments for an old problem. Lancet Infect Dis. 2018; 18(4):e107–e118.
Epub 2018/02/06. https://doi.org/10.1016/S1473-3099(18)30066-5 PMID: 29396010.
14. World Health Organization. World malaria report 2021 2021 [cited 2022 February 15]. Available from:
https://www.who.int/publications/i/item/9789240040496.
15. McElfish PA, Ayers BL, Purvis RS, Long CR, Esquivel M, Steelman SC. Best practices for community-
engaged participatory research with Pacific Islander communities in the USA and USAPI: protocol for a
PLOS GLOBAL PUBLIC HEALTH
Preterm birth prevalence among Pacific Islanders: A meta-analysis
PLOS Global Public Health | https://doi.org/10.1371/journal.pgph.0001000 June 14, 2023 15 / 19
scoping review. BMJ Open. 2018; 8(1). https://doi.org/10.1136/bmjopen-2017-019653 PMID:
29371285
16. Ayers BL, Hawley NL, Purvis RS, Moore SJ, McElfish PA. Providers’ perspectives of barriers experi-
enced in maternal health care among Marshallese women. Women Birth. 2018; 31(5):e294–e301.
https://doi.org/10.1016/j.wombi.2017.10.006 PMID: 29126795
17. George S, Duran N, Norris K. A systematic review of barriers and facilitators to minority research partici-
pation among African Americans, Latinos, Asian Americans, and Pacific Islanders. Am J Public Health.
2014; 104(2):e16–e31. https://doi.org/10.2105/AJPH.2013.301706 PMID: 24328648
18. McElfish PA, Narcisse M-R, Long CR, Ayers BL, Hawley NL, Aitaoto N, et al. Leveraging community-
based participatory research capacity to recruit Pacific Islanders into a genetics study. J Community
Genet. 2017; 8(4):283–291. https://doi.org/10.1007/s12687-017-0313-9 PMID: 28689351
19. Sorkin DH, Ngo-Metzger Q, De Alba I. Racial/ethnic discrimination in health care: impact on perceived
quality of care. J Gen Intern Med. 2010; 25(5):390–396. https://doi.org/10.1007/s11606-010-1257-5
PMID: 20146022
20. Wu B, Arslanian KJ, Nyhan K, Taylor S, Shabanova V, Muasau-Howard B, et al. Preterm birth among
Pacific Islander women and related perinatal outcomes: a scoping review protocol. BMJ Open. 2021;
11(11):e050483. https://doi.org/10.1136/bmjopen-2021-050483 PMID: 34728448
21. Moher D, Liberati A, Tetzlaff J, Altman DG, Altman D, Antes G, et al. Preferred reporting items for sys-
tematic reviews and meta-analyses: the PRISMA statement (Chinese edition). J Chin Integr Med. 2009;
7(9):889–896.
22. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observa-
tional studies in epidemiology: a proposal for reporting. Jama. 2000; 283(15):2008–2012.
23. World Health Organization. Pacific Island Countries 2013 [cited 2020 Aug]. Available from: https://apps.
who.int/iris/bitstream/handle/10665/136831/ccsbrief_pci_en.pdf?sequence=1&isAllowed=y.
24. Bohao Wu KA, Nyhan Kate, Taylor Sarah, Shabanova Veronika, Muasau-Howard Bethel, Hawley
Nicola. Preterm Birth among Pacific Islander Women and Related Perinatal Outcomes: a Scoping
Review Protocol 2020 [cited 2022 February 15]. Available from: https://osf.io/8x74v/.
25. Joanna Briggs Institute. Critical Appraisal Tools [cited 2021 May 5]. Available from: https://jbi.global/
critical-appraisal-tools.
26. Munn Z, Moola S, Lisy K, Riitano D, Tufanaru C. Methodological guidance for systematic reviews of
observational epidemiological studies reporting prevalence and cumulative incidence data. Int J Evid
Based Healthc. 2015; 13(3):147–153. https://doi.org/10.1097/XEB.0000000000000054 PMID:
26317388
27. Moola S, Munn Z, Tufanaru C, Aromataris E, Sears K, Sfetcu R, et al. Chapter 7: Systematic reviews of
etiology and risk 2017 [cited 2021 May 5]. Available from: https://synthesismanual.jbi.global
28. Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test.
Br Med J. 1997; 315(7109):629–634. https://doi.org/10.1136/bmj.315.7109.629 PMID: 9310563
29. Vevea JL, Woods CM. Publication bias in research synthesis: sensitivity analysis using a priori weight
functions. Psychol Methods. 2005; 10(4):428–443. Epub 2006/01/06. https://doi.org/10.1037/1082-
989X.10.4.428 PMID: 16392998.
30. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986; 7(3):177–188. https://
doi.org/10.1016/0197-2456(86)90046-2 PMID: 3802833
31. Barker TH, Migliavaca CB, Stein C, Colpani V, Falavigna M, Aromataris E, et al. Conducting propor-
tional meta-analysis in different types of systematic reviews: a guide for synthesisers of evidence. BMC
Med Res Methodol. 2021; 21(1):1–9.
32. Ru¨cker G, Schwarzer G, Carpenter JR, Schumacher M. Undue reliance on I 2 in assessing heterogene-
ity may mislead. BMC Med Res Methodol. 2008; 8(1):1–9.
33. von Hippel PT. The heterogeneity statistic I2 can be biased in small meta-analyses. BMC Med Res
Methodol. 2015; 15(1):1–8. https://doi.org/10.1186/s12874-015-0024-z PMID: 25880989
34. Example—Random-Effects Method [cited 2022 February 13]. Available from: http://www.cebm.brown.
edu/openmeta/doc/random_effects_example.html#top.
35. Ro
¨ver C. Bayesian random-effects meta-analysis using the bayesmeta R package. arXiv preprint
arXiv:171108683. 2017.
36. Schwarzer G, Schwarzer MG. Package ‘meta’ 2012 [cited 2021 April 10]. Available from: https://mirror-
hk.koddos.net/CRAN/web/packages/meta/meta.pdf.
37. Harrer M, Cuijpers P, Furukawa T, Ebert DD. dmetar: Companion R Package For The Guide ’Doing
Meta-Analysis in R’ 2019 [cited 2021 April 10]. Available from: http://dmetar.protectlab.org/.
PLOS GLOBAL PUBLIC HEALTH
Preterm birth prevalence among Pacific Islanders: A meta-analysis
PLOS Global Public Health | https://doi.org/10.1371/journal.pgph.0001000 June 14, 2023 16 / 19
38. Roever C, Friede T. Package ‘bayesmeta’ 2017 [cited 2022 January 4]. Available from: https://cran.uib.
no/web/packages/bayesmeta/bayesmeta.pdf.
39. Bartos
ˇF. Package ’RoBMA’ 2022 [cited 2022 February 8]. Available from: https://cran.r-project.org/
web/packages/RoBMA/RoBMA.pdf.
40. Guan M, Vandekerckhove J. A Bayesian approach to mitigation of publication bias. Psychon Bull Rev.
2016; 23(1):74–86. https://doi.org/10.3758/s13423-015-0868-6 PMID: 26126776
41. Wartko PD, Wong EY, Enquobahrie DA. Maternal birthplace is associated with low birth weight within
racial/ethnic groups. Matern Child Health J. 2017; 21(6):1358–1366. https://doi.org/10.1007/s10995-
016-2241-4 PMID: 28093687
42. Nembhard WN, Ayers BL, Collins RT, Shan X, Rabie NZ, Chang D, et al. Adverse pregnancy and neo-
natal outcomes among Marshallese women living in the United States. Matern Child Health J. 2019; 23
(11):1525–1535. https://doi.org/10.1007/s10995-019-02775-8 PMID: 31228148
43. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK. Births: Final Data for 2018. Natl Vital Stat Rep.
2019; 68(13):1–47. Epub 2020/06/06. PMID: 32501202.
44. Korinek K, Ahmmad Z. The Racial Configuration of Parent Couples and Premature Birth: an Analysis of
the Utah Population Database. J Racial Ethn Health Disparities. 2021:1–15.
45. Hirai AH, Hayes DK, Taualii MM, Singh GK, Fuddy A, Loretta J. Excess infant mortality among Native
Hawaiians: identifying determinants for preventive action. Am J Public Health. 2013; 103(11):e88–e95.
https://doi.org/10.2105/AJPH.2013.301294 PMID: 24028241
46. Hamilton BE, Martin JA, Osterman MJ. Births: Provisional data for 2020. 2021.
47. Crowell DH, Sharma SD, Seto D, Baruffi G, Dunn-Rankin P, Dong J. Samoan parental ethnicity and
infant birth-weight in Hawai’i. Hawaii Med J. 2007; 66(1). PMID: 17381034
48. Andrasfay T. Birth Outcomes among Descendants of Foreign-Born and US-Born Women in California:
Variation by Race and Ethnicity. J Immigr Minor Health. 2021:1–9. https://doi.org/10.1007/s10903-021-
01221-8 PMID: 34075511
49. Altman MR, Baer RJ, Jelliffe-Pawlowski LL. Patterns of preterm birth among women of native Hawaiian
and Pacific Islander Descent. Am J Perinatol. 2019; 36(12):1256–1263. https://doi.org/10.1055/s-0038-
1676487 PMID: 30577054
50. Hawaii State Department of Health. Hawaii Pregnancy Risk Assessment Monitoring System (PRAMS):
Hawaii State Department of Health; 2019 [cited 2021 May 17]. Available from: https://health.hawaii.gov/
fhsd/files/2019/07/PRAMS-Trend-Report-ALL-FINAL6-2019-LR.pdf.
51. Seattle & King County Public Health. Health of Mothers and Infants by Race/Ethnicity 2015 [cited 2021
May 17]. Available from: https://www.kingcounty.gov/depts/health/data/~/media/depts/health/data/
documents/Health-of-Mothers-and-Infants-by-Race-Ethnicity.ashx.
52. Centers for Disease Control and Prevention. Maternal, pregnancy, and birth characteristics of Asians
and Native Hawaiians/Pacific Islanders—King County, Washington, 2003–2008. MMWR Morb Mortal
Wkly Rep. 2011; 60(7):211–213. PMID: 21346708
53. Hamilton BE, Martin JA, Osterman MJ. Births: Provisional data for 2021. 2022.
54. Republic of the Marshall Islands. "Kumiti Ejmuur" annual report FY 2010 2010 [cited 2021 November
20]. Available from: https://rmihealth.org/attachments/article/189/
FY2010AnnualHealthDataReportFinal_2010.pdf.
55. Republic of the Marshall Islands Ministry of Health. Fiscal year 2016 annual report 2016 [cited 2021
November 20]. Available from: https://rmihealth.org/attachments/article/192/FY2016%20MOH%
20Summary%20Report_2016.pdf.
56. Berger KE, Masterson J, Mascardo J, Grapa J, Appanaitis I, Temengil E, et al. The effects of chewing
betel nut with tobacco and pre-pregnancy obesity on adverse birth outcomes among Palauan women.
Matern Child Health J. 2016; 20(8):1696–1703. https://doi.org/10.1007/s10995-016-1972-6 PMID:
26994610
57. Cruz RD, Grant J, Heck JE, Cash HL. Peer Reviewed: Disparities in Adverse Perinatal Outcomes
Among Pacific Islanders in the Commonwealth of the Northern Mariana Islands. Prev Chronic Dis.
2018;15.
58. Fox AM, Parker T, Palmer KS. Prenatal care in the Commonwealth of the Northern Mariana Islands.
Pac Health Dialog. 2005; 12(1):67–74. PMID: 18181466
59. Wright S, Mitchell E, Thompson J, Clements M, Ford R, Stewart A. Risk factors for preterm birth: a New
Zealand study. N Z Med J. 1998; 111(1058):14–16. PMID: 9484428
60. Sundborn G, Schluter PJ, Schmidt-Uili M, Paterson J. What defines ‘Low birth weight’in Pacific infants
born in New Zealand? AUT Pacific Islands Families Study Of those Born in 2000, at Manukau City, New
Zealand. 2011; 17(2):23.
PLOS GLOBAL PUBLIC HEALTH
Preterm birth prevalence among Pacific Islanders: A meta-analysis
PLOS Global Public Health | https://doi.org/10.1371/journal.pgph.0001000 June 14, 2023 17 / 19
61. Sadler L, McCowan L, Stone P. Associations between ethnicity and obstetric intervention in New Zea-
land. 2002.
62. Lawton B, Stanley J, Filoche S, Garrett S, Rose SB, Robson B, et al. Exploring the maternal and infant
continuum–ethnic disparities in infant hospital admissions for respiratory disease. Aust N Z J Public
Health. 2016; 40(5):430–435. https://doi.org/10.1111/1753-6405.12505 PMID: 27027513
63. Cantwell R. A prospective study of Maori infant health and the problem of nutritional anaemia. N Z Med
J. 1973; 78(495):61–65. PMID: 4542745
64. Berry MJ, Foster T, Rowe K, Robertson O, Robson B, Pierse N. Gestational age, health, and educa-
tional outcomes in adolescents. Pediatrics. 2018;142(5). https://doi.org/10.1542/peds.2018-1016
PMID: 30381471
65. Ministry of Health New Zealand. Fetal and Infant Deaths 2016 2019 [cited 2023 March 30]. Available
from: https://www.health.govt.nz/publication/fetal-and-infant-deaths-2016.
66. Mozooni M, Preen DB, Pennell CE. Stillbirth in Western Australia, 2005–2013: the influence of maternal
migration and ethnic origin. Med J Aust. 2018; 209(9):394–400. https://doi.org/10.5694/mja18.00362
PMID: 30282563
67. Ye Berman, Ibiebele I, Randall D, Torvaldsen S, Nippita TA, Bowen J, et al. Rates of neonatal morbidity
by maternal region of birth and gestational age in New South Wales, Australia 2003-2016. Acta Obstet
Gynecol Scand. 2021; 100(2):331–338. https://doi.org/10.1111/aogs.14012 PMID: 33007108
68. Allen S, Raiko A, O’Donnell A, Alexander N, Clegg J. Causes of preterm delivery and intrauterine growth
retardation in a malaria endemic region of Papua New Guinea. Arch Dis Child Fetal Neonatal Ed. 1998;
79(2):F135–F140. https://doi.org/10.1136/fn.79.2.f135 PMID: 9828741
69. Garner P, Dubowitz L, Baea M, Lai D, Dubowitz M, Heywood P. Birthweight and gestation of village
deliveries in Papua New Guinea. J Trop Pediatr. 1994; 40(1):37–39. https://doi.org/10.1093/tropej/40.1.
37 PMID: 8182780
70. Senn M, Baiwog F, Winmai J, Mueller I, Rogerson S, Senn N. Betel nut chewing during pregnancy,
Madang province, Papua New Guinea. Drug Alcohol Depend. 2009; 105(1–2):126–131. https://doi.org/
10.1016/j.drugalcdep.2009.06.021 PMID: 19665325
71. Unger HW, Rosanas-Urgell A, Robinson LJ, Ome-Kaius M, Jally S, Umbers AJ, et al. Microscopic and
submicroscopic Plasmodium falciparum infection, maternal anaemia and adverse pregnancyoutcomes
in Papua New Guinea: a cohort study. Malar J. 2019; 18(1):1–9.
72. Cafaro J, Randle E, Wyche P, Higgins M, Fink J, Jones PD. An assessment of current antenatalcare
practices and identification of modifiable risk factors for prematurity and low birth weight infants in preg-
nancy in Solomon Islands. Rural Remote Health. 2015; 15(3):[369]–[371]. PMID: 26363609
73. Therrien AS, Buffa G, Roome AB, Standard E, Pomer A, Obed J, et al. Relationships between mental
health and diet during pregnancy and birth outcomes in a lower-middle income country:“Healthy moth-
ers, healthy communities” study in Vanuatu. American Journal of Human Biology. 2021; 33(3):e23500.
https://doi.org/10.1002/ajhb.23500 PMID: 32918311
74. Ratnasiri AW, Parry SS, Arief VN, DeLacy IH, Lakshminrusimha S, Halliday LA, et al. Temporal trends,
patterns, and predictors of preterm birth in California from 2007 to 2016, based on the obstetric estimate
of gestational age. Matern Health Neonatol Perinatol. 2018; 4(1):1–19. https://doi.org/10.1186/s40748-
018-0094-0 PMID: 30564431
75. Schempf AH, Mendola P, Hamilton BE, Hayes DK, Makuc DM. Perinatal outcomes for Asian, Native
Hawaiian, and other Pacific Islander mothers of single and multiple race/ethnicity: California and Hawaii,
2003–2005. Am J Public Health. 2010; 100(5):877–887. https://doi.org/10.2105/AJPH.2009.177345
PMID: 20299645
76. Craig ED, Mantell CD, Ekeroma AJ, Stewart AW, Mitchell EA. Ethnicity and birth outcome: New Zea-
land trends 1980–2001. Part 1. Introduction, methods, results and overview. Aust N Z J Obstet Gynae-
col. 2004; 44(6):530–536. Epub 2004/12/16. https://doi.org/10.1111/j.1479-828X.2004.00309.x PMID:
15598291.
77. Edmonds LK, Sibanda N, Geller S, Cram F, Robson B, Filoche S, et al. He Tamariki Kokoti Tau: Tack-
ling preterm incidence and outcomes of preterm births by ethnicity in Aotearoa New Zealand 2010–
2014. Int J Gynaecol Obstet. 2021; 155(2):239–246. https://doi.org/10.1002/ijgo.13855 PMID:
34355389
78. Parry GK. Ethnic and Maternal Determinants of Fetal Growth in Normal Pregnancies: University of
Auckland; 2011.
79. Mathews T, Menacker F, MacDorman MF. Infant mortality statistics from the 2001 period linked birth/
infant death data set. Natl Vital Stat Rep. 2003; 52(2):1–28. PMID: 14518553
PLOS GLOBAL PUBLIC HEALTH
Preterm birth prevalence among Pacific Islanders: A meta-analysis
PLOS Global Public Health | https://doi.org/10.1371/journal.pgph.0001000 June 14, 2023 18 / 19
80. Wong LF, Caughey AB, Nakagawa S, Kaimal AJ, Tran SH, Cheng YW. Perinatal outcomes among dif-
ferent Asian-American subgroups. Am J Obstet Gynecol. 2008; 199(4):382. e381–382. e386. https://
doi.org/10.1016/j.ajog.2008.06.073 PMID: 18722570
81. Quan NS, Kramer MR. Revealing the variations in impact of economic segregation on preterm birth
among disaggregated Asian ethnicities across MSAs in the United States: 2015–2017. SSM Popul
Health. 2021; 14:100813. https://doi.org/10.1016/j.ssmph.2021.100813 PMID: 34041352
82. World Health Organization. Global preterm birth estimaes [cited 2021 January]. Available from: https://
ptb.srhr.org/.
83. U.S. Department of Health and Human Services Office of Minority Health. Profile: Native Hawaiians/
Pacific Islanders [cited 2022 May]. Available from: https://minorityhealth.hhs.gov/omh/browse.aspx?
lvl=3&lvlid=65#:~:text=According%20to%20the%202019%20U.S.,percent%20of%20the%20U.S.%
20population.
84. Ministry of Health in New Zealand. Very Low Cost Access scheme 2020 [cited 2022 February 14]. Avail-
able from: https://www.health.govt.nz/our-work/primary-health-care/primary-health-care-subsidies-
and-services/very-low-cost-access-scheme.
85. Ministry of Health in New Zealand. Te Tiriti o Waitangi [cited 2022 February 14]. Available from: https://
www.health.govt.nz/our-work/populations/maori-health/te-tiriti-o-waitangi.
86. Durie M. An Indigenous model of health promotion. Health Promot J Austr. 2004; 15(3):181–185.
87. Goodyear-Smith F, Ashton T. New Zealand health system: universalism struggles with persisting ineq-
uities. Lancet. 2019; 394(10196):432–442. https://doi.org/10.1016/S0140-6736(19)31238-3 PMID:
31379334
88. Hobbs M, Ahuriri-Driscoll A, Marek L, Campbell M, Tomintz M, Kingham S. Reducing health inequity for
Māori people in New Zealand. Lancet. 2019; 394(10209):1613–1614.
89. Chin MH, King PT, Jones RG, Jones B, Ameratunga SN, Muramatsu N, et al. Lessons for achieving
health equity comparing Aotearoa/New Zealand and the United States. Health Policy. 2018; 122
(8):837–853. https://doi.org/10.1016/j.healthpol.2018.05.001 PMID: 29961558
90. Australian Government Department of Foreign Affairs and Trade. Strengthening Pacific health systems:
evaluating ten years of Australia’s support [cited 2022 May]. Available from: https://www.dfat.gov.au/
sites/default/files/pacific-health-evaluation.pdf.
91. Farrant BM, Shepherd CC. Maternal ethnicity, stillbirth and neonatal death risk in Western Australia
1998–2010. Aust N Z J Obstet Gynaecol. 2016; 56(5):532–536. https://doi.org/10.1111/ajo.12465
PMID: 27135304
92. Robbins C, Martocci S. Timing of prenatal care initiation in the Health Resources and Services Adminis-
tration Health Center Program in 2017. Ann Intern Med. 2020; 173(11_Supplement):S29–S36.
93. Association of State and Territorial Health Officials. ASTHO US-Affiliated Pacific Islands (USAPI) Pro-
file Report 2012 [cited 2022 May]. Available from: https://opioidspreparedness.org/Profile/Volume-
Three/US-Affiliated-Pacific-Islands/.
94. Health Resources and Services Administration. III.E.2.c. State Action Plan—Perinatal/Infant Health—
Annual Report—Northern Mariana Islands—2022 2022 [cited 2022 May]. Available from: https://mchb.
tvisdata.hrsa.gov/Narratives/AnnualReport2/a4a44ac0-0122-411a-b402-9023679581fe.
95. Cha S, Malik T, Abara WE, DeSimone MS, Schumann B, Mallada E, et al. Screening for Syphilis and
Other Sexually Transmitted Infections in Pregnant Women—Guam, 2014. Morb Mortal Wkly Rep.
2017; 66(24):644. https://doi.org/10.15585/mmwr.mm6624a4 PMID: 28640799
96. The World Bank. Population, total—Papua New Guinea [cited 2022 June]. Available from: https://data.
worldbank.org/indicator/SP.POP.TOTL?locations=PG.
97. Andrew EV, Pell C, Angwin A, Auwun A, Daniels J, Mueller I, et al. Factors affecting attendance at and
timing of formal antenatal care: results from a qualitative study in Madang, Papua New Guinea. PLoS
One. 2014; 9(5):e93025. https://doi.org/10.1371/journal.pone.0093025 PMID: 24842484
98. Davy C. Primary health care: knowledge development and application in Papua New Guinea 2009.
PLOS GLOBAL PUBLIC HEALTH
Preterm birth prevalence among Pacific Islanders: A meta-analysis
PLOS Global Public Health | https://doi.org/10.1371/journal.pgph.0001000 June 14, 2023 19 / 19
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