CLINICAL STUDY PROTOCOL
published: 01 June 2022
doi: 10.3389/fpubh.2022.890381
Study Protocol: Interactive Dynamics
of Coral Reef Fisheries and the
Nutrition Transition in Kiribati
Christopher D. Golden 1,2*† , Julien Ayroles 3† , Jacob G. Eurich 4,5† , Jessica A. Gephart 6† ,
Katherine L. Seto 7† , Michael K. Sharp 8,9† , Prentiss Balcom 10 , Haley M. Barravecchia 2 ,
Keegan K. Bell 4 , Kelvin D. Gorospe 6 , Joy Kim 11 , William H. Koh 1 ,
Jessica Zamborain-Mason 1 , Douglas J. McCauley 4 , Helen Murdoch 12 , Nilendra Nair 1 ,
Kaaro Neeti 12 , Simone Passarelli 1 , Aaron Specht 2 , Elsie M. Sunderland 10 ,
Aritita Tekaieti 13 , Aranteiti Tekiau 14 , Rosemary Tekoaua 12 and Eretii Timeon 12
1
Edited by:
Stephanie Norman,
Marine-Med: Marine Research,
Epidemiology and Veterinary
Medicine, United States
Reviewed by:
Brian McAdoo,
Duke University, United States
Vik Mohan,
Blue Ventures, United Kingdom
*Correspondence:
Christopher D. Golden
golden@hsph.harvard.edu
† These
authors share first authorship
Specialty section:
This article was submitted to
Planetary Health,
a section of the journal
Frontiers in Public Health
Received: 05 March 2022
Accepted: 11 May 2022
Published: 01 June 2022
Citation:
Golden CD, Ayroles J, Eurich JG,
Gephart JA, Seto KL, Sharp MK,
Balcom P, Barravecchia HM, Bell KK,
Gorospe KD, Kim J, Koh WH,
Zamborain-Mason J, McCauley DJ,
Murdoch H, Nair N, Neeti K,
Passarelli S, Specht A,
Sunderland EM, Tekaieti A, Tekiau A,
Tekoaua R and Timeon E (2022) Study
Protocol: Interactive Dynamics of
Coral Reef Fisheries and the Nutrition
Transition in Kiribati.
Front. Public Health 10:890381.
doi: 10.3389/fpubh.2022.890381
Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States, 2 Department of
Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States, 3 Department of Ecology &
Evolutionary Biology, Princeton University, Princeton, NJ, United States, 4 Marine Sciences Institute, University of California,
Santa Barbara, Santa Barbara, CA, United States, 5 Environmental Defense Fund, Santa Barbara, CA, United States,
6
Department of Environmental Science, American University, Washington, DC, United States, 7 Department of Environmental
Studies, University of California, Santa Cruz, Santa Cruz, CA, United States, 8 Statistics for Development Division, Pacific
Community, Noumea, New Caledonia, 9 Australian National Centre for Ocean Resources and Security, University of
Wollongong, Wollongong, NSW, Australia, 10 School of Engineering and Applied Sciences, Harvard University, Cambridge,
MA, United States, 11 BAO Systems, Washington, DC, United States, 12 Ministry of Health and Medical Services, Tarawa,
Kiribati, 13 National Statistics Office, Ministry of Finance and Economic Development, Tarawa, Kiribati, 14 Ministry of Fisheries
and Marine Resources Development, Tarawa, Kiribati
The Kiribati 2019 Integrated Household Income and Expenditure Survey (Integrated
HIES) embeds novel ecological and human health research into an ongoing social and
economic survey infrastructure implemented by the Pacific Community in partnership
with national governments. This study seeks to describe the health status of a large,
nationally representative sample of a geographically and socially diverse I-Kiribati
population through multiple clinical measurements and detailed socio-economic surveys,
while also conducting supporting food systems research on ecological, social, and
institutional drivers of change. The specific hypotheses within this research relate to
access to seafood and the potential nutritional and health benefits of these foods. We
conducted this research in 21 of the 23 inhabited islands of Kiribati, excluding the two
inhabited islands—Kanton Islands in the Phoenix Islands group with a population of 41
persons (2020 census) and Banaba Island in the Gilbert Islands group with a population
of 333 persons (2020 census)—and focusing exclusively on the remaining islands in
the Gilbert and Line Islands groups. Within this sample, we focused our intensive human
health and ecological research in 10 of the 21 selected islands to examine the relationship
between ecological conditions, resource governance, food system dynamics, and dietary
patterns. Ultimately, this research has created a baseline for future Integrated HIES
assessments to simultaneously monitor change in ecological, social, economic, and
human health conditions and how they co-vary over time.
Keywords: food security, planetary health, small island developing state (SIDS), diabetes, obesity, hypertension,
social-ecological traps, traditional diets
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INTRODUCTION
ranges from densely populated, urban islands with heavy reef
degradation to sparsely populated and remote outer islands with
intact marine systems e.g., 5,200 people/km2 in South Tarawa
as compared to 300 people/km2 in South Tabiteuea (12, 13).
This gradient of human pressure provides a lens to assess
disturbances to reef systems. Local drivers of environmental
degradation, such as fishing pressure, reef rock mining, landuse changes (e.g., sedimentation due to shoreline manipulation),
nutrient run-off (e.g., sewage), and pollution, showcase the
effects of population growth in urban centers (12). These
patterns will likely increase with efforts to supply seafood to the
burgeoning demand in domestic urban markets (14), as even
urban islands like South Tarawa produce nearly half of their
seafood from reefs. Specifically, signs of overexploitation in the
lagoon and fore reefs from artisanal and subsistence fisheries can
be seen around the main communities of South Tarawa (15),
with surrounding islands beginning to lose flagship ecological
indicators of a healthy reef system (see Data Analysis for a
comprehensive description).
Globally, aquatic food systems support livelihoods and nutrition
for billions of people (1). These benefits are derived both
directly (e.g., consuming aquatic foods for better nutrition or
catching and selling aquatic foods for income) and indirectly
(e.g., using income derived from fishing livelihoods to support
better nutrition). Yet, questions remain about the sustainability
of aquatic food systems and their ability to continue delivering
benefits to people (2). Approximately 1 billion people rely
substantially on aquatic foods and could be placed at increased
risk of nutritional deficiencies with ongoing environmental and
socio-economic change (3). Quantifying the nutritional impact
of different sources of environmental change (e.g., unsustainable
fishing, climate change, coral bleaching), however, has been
difficult in part because these system dynamics are complex,
containing multiple direct, and indirect pathways and feedbacks.
We applied a social-ecological systems (SES) framework to
study how feedbacks and interactive dynamics across social
and ecological dimensions of coral reef food systems lead to
differences in nutritional ecology [sensu (4)] of malnutrition and
diet-related disease (5). In this system, we believe that reinforcing
social and environmental changes have led to changes in food
systems, and in turn, have led to changes in human health
outcomes. We focused on reef-based food systems in Kiribati as
a case study for several reasons. Seafood consumption in Kiribati
is ∼63 kg/person/year (6)—one of the highest in the world, and
with high dependence on reef-based resources (7). In systems
where aquatic foods are critical for nutrition and aquaculture
is absent (8), such as nutritionally vulnerable countries, smallscale fisheries are a key sector to meet many dietary requirements.
Reef-based foods are part of small-scale fisheries, and thus almost
entirely retained in domestic markets (9, 10).
The geographic isolation of the country (and even greater
isolation of some of its constituent islands) allowed us to
examine the role of globalization and market integration in
shaping food system dynamics in a more controlled way. Due
to Kiribati’s geographic diversity, a range of market, governance,
and ecological circumstances exist, allowing for strong inter- and
intra-island comparisons within the same national context.
Climate Change in Kiribati
As with many other low-lying atoll nations, climate change is
forecasted to create a multitude of development and adaptation
challenges in Kiribati. The magnitude and timing of these local
impacts and the best adaptation pathways to address these
global climate stressors are complex (16–18). Specifically, with
increasing sea levels (14) and increasing frequency and severity
of strong westerlies during El Niño Southern Oscillation (ENSO)
episodes (19), storm surges have been more common (12)
resulting in seawater contamination of freshwater resources (20)
and sewage and fertilizer runoff into coastal areas. Further,
Kiribati climate models indicate with “very high confidence”
that both sea surface and air temperatures are increasing and
will continue to do so throughout the twenty-first century
(21). Increased sea surface temperatures above usual thresholds
can result in coral bleaching which may lead to a benthic
shift to stress tolerant coral species (22). In Kiribati, bleaching
events have been recorded during extreme ENSO conditions
in 2004–2005 and in 2009–2010, although the severity of coral
bleaching was limited in 2009–2010 (23). Bleaching events may
reduce structural complexity which provides critical habitat for
fishes and protects against waves and storm surges—two critical
ecosystem services (24). Urban areas may have combined impacts
from climate change and human activity that could destabilize
coral communities (23, 25). On outer islands with less human
disturbance, coral communities maintain high diversity, but
remain vulnerable to large-scale bleaching events and other local
stressors (12).
Environmental Change in Kiribati
Due to the geological constraints of low-lying coral reef
atolls, Kiribati relies heavily on its marine resources for food
security. With a lack of arable land, people depend on local
reef and pelagic fisheries as a source of nutrition. However,
anthropogenic influences have placed significant pressure on the
nation’s immediate coastal marine environment (11). The nation
Economic Change in Kiribati
Abbreviations: AU, American University; BR, back reef; FR, fore reef; HIES,
Household Income and Expenditure Survey; HSPH, Harvard T.H. Chan School of
Public Health; KNSO, Kiribati National Statistics Office; LR, lagoon reef; MFMRD,
Ministry of Fisheries and Marine Resource Development; MHMS, Ministry of
Health and Medical Services; MT, manta tow; SIQ, soft-infaunal quadrat; SPC,
Pacific Community, formerly known as the Secretariat of the Pacific Community;
UCSB, University of California, Santa Barbara; UCSC, University of California,
Santa Cruz; UW, University of Wollongong; USD, United States Dollar; GDP,
Gross domestic product.
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Pacific island economies have historically been dominated by
subsistence and small-scale economic activities, with diets largely
based on local foods, including seafood, root crops, starchy
fruits, leafy greens, and coconut products (26). This is in part
because the geographic isolation of island nations makes trade
in perishable goods logistically challenging and costly. Yet, food
imports, especially ultra-processed foods (e.g., sugar-sweetened
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Reef Fisheries and Human Nutrition
neurological, cardiovascular, and gastrointestinal human health
impacts can occur, with extreme cases resulting in fatality (38). In
Kiribati, there are known high-risk areas where previous studies
have found toxic concentrations (40), but little is known about
the spatial variation, species of high-risk, and how long areas
with known ciguatera outbreaks persist [but see (14, 40, 42)].
Our research will examine the prevalence, concentration, and
distribution of ciguatera in marine food webs, and how this
relates to dietary behaviors.
beverages, ramen, spam), have increased throughout the Pacific,
including in Kiribati (27). From 1961 to 2019, food imports
to Kiribati outpaced population growth, with imports growing
by 4 times (in terms of inflation-adjusted value; 27), while
population grew by 2.8 times (28). Increasing imports is a result
of—and reinforcing factor in—the shift toward a cash-based
economy, urbanization, export promotion, financial integration,
and development aid (29). These concurrent economic shifts are
reflected in the percent of the population living in urban areas in
Kiribati, which increased from <17% in 1961 to over 54% in 2019
(30), and increases in agricultural and fishery commodity exports,
especially fish and coconut product exports (31). Collectively,
these changes point toward a transition in market structure that is
shifting the foods available and being consumed in Kiribati, with
some I-Kiribati populations increasingly consuming more high
fat and sugary processed foods (6).
Health Change in Kiribati
The impact of the above-mentioned economic, environmental,
and climatic changes will pose threats to food availability,
income generation, and local ecosystems, potentially affecting
the nutritional status and associated disease burden of I-Kiribati.
These health transitions have been well-articulated globally (43)
and have particular importance in the Pacific, where declining
infectious disease burdens are accompanied by increases in noncommunicable diseases, or “diseases of modernization” (44).
These transitions are largely driven by shifts in dietary patterns
(5, 45, 46) and are often characterized by a reduction in
undernourishment and a simultaneous rise in overnutrition (47).
Water Quality
Marine pollution from land-based point sources (e.g., landfills,
industrial waste, and sewage outfalls) and non-point sources (e.g.,
solid waste from humans and animals, heavy metals, wastewater,
leaking septic tanks, pesticides, and fertilizers) are considered to
be a primary threat to Kiribati coral reefs and thus, I-Kiribati
health (12). Despite mercury and other heavy metals occurring in
the environment naturally, anthropogenic sources such as urban
runoff and pollution influence local levels and are considered a
threat to coral reefs (32). Mercury is a ubiquitous metal in the
environment that can have negative health effects, with seafood
consumption a major source of human exposure due to its
bioaccumulation across marine species food webs (33). While
mercury exposure and levels of risk can vary due to human
cultural practices (including eating), genetics, and ethnicity (34),
even low doses can cause chronic issues (35). In Kiribati, there is
limited mercury, heavy metal, and microbiological information
[e.g., (36)], despite the very high consumption of seafood of IKiribati, and heavy dependence on reef-based resources. This
study provides the first broad-scale assessment of mercury and
heavy metals in plants, reef fish, and humans across multiple
islands and reef habitats of Kiribati.
METHODS/DESIGN
Study Aims
In this study, we aimed to (1) quantify the prevalence and
variation of nutrition-related disease risk within and among
islands; (2) characterize the external social-ecological risk factors
that could shape disease status, including environmental health,
food availability, and market access; (3) characterize the internal
genetic and physiological risk factors that could shape disease
status; and (4) analyze associations between these risk factors
and nutrition-related disease at the individual, household,
community, island, and national scale. It is also our hope to
establish a baseline for future longitudinal research.
Study Design and Setting
We launched this study in the Republic of Kiribati, an
independent nation of 33 low-lying islands in the central Pacific
Ocean (Figure 1). The nation comprises three major island
groups: the westernmost Gilbert Islands group, the sparsely
inhabited central Phoenix Island group, and the easternmost Line
Islands group. While Kiribati has a total land area of 811 km2
distributed throughout these three groups, it also encompasses
∼3.55 million km2 of ocean area within their Exclusive Economic
Zone, representing the largest ocean-to-land ratio in the world
(48). Kiribati has a population of ∼120,000 people, ∼50% of
which lives on the main Gilbert Island and capital of Kiribati,
South Tarawa, and a per capita GDP of $1,636 USD, 9–16% of
which emerges from fishing and related sectors (48–50).
Our mixed-method approach was embedded in a previously
planned, nationally representative, observational cross-sectional
study called the Household Income and Expenditure Survey
(HIES) (50). The HIES is the equivalent to a Household Budget
Survey, Household Expenditure and Consumption Survey, or
a Living Standard Measurement Survey, which are generally
Ciguatera
The incidence of ciguatera outbreaks, a food-borne illness
produced from the dinoflagellate Gambierdiscus spp., can become
more frequent as reefs degrade and algal growth increases (20,
37). Gambierdiscus spp. settle on the benthic substrate, such as
algal turf or dead branching corals, and produce a ciguatoxin
naturally (38, 39). The dinoflagellate is consumed passively
as small-bodied reef fish graze resulting in the ciguatoxin
bioaccumulating up the food chain following predation from
larger bodied species (40). Thus, the incidence of ciguatera in
reef fish catch can become more prevalent when reef degradation
increases after a bleaching event or following nutrient input
from anthropogenic sources (38, 41). For nations dependent
on seafood, like Kiribati, ciguatera can have a profound
impact on food security as there are scarce animal-source food
alternatives if a ciguatera outbreak occurs (39). If a fish with
high concentrations of ciguatoxin is consumed knowingly or not,
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FIGURE 1 | Map of the study area in the Republic of Kiribati.
Creating the Integrated HIES
conducted by all countries. The Pacific HIES is conducted
by the Statistics Office of each national government, through
technical and financial support from the Pacific Community
(SPC), World Bank, the Food and Agriculture Organization of
the United Nations and the International Labor Organization.
The HIES collects information on household consumption and
income, with the explicit purpose of estimating poverty and
income distribution at national scales, and to rebase GDP and
the basket of goods used in the calculation of the Consumer
Price Index.
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Our research integrates four separate research modules and
is hereafter called the Integrated HIES. The first module was
the original, standard HIES, which provides the demographic,
social, and economic context to our broader research goals. The
second module featured marine ecological research on the health
and status of the coral reef system and associated ecological
indicators. The third module focused on deepening the social,
institutional, and economic dynamics that collectively shape
local markets, and analyzed marine governance as a driver of
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require water transport to access the airport and/or central hub,
which contains the Island Council and government buildings,
were excluded. These included, but were not limited to, villages
on coral cays, islets, or coral islands that were not connected
by existing infrastructure. Villages additionally were selected
to be geographically similar, where possible. Specifically, most
Kiribati communities are located on the leeward (West) lagoonfacing side of the coral atoll arm adjacent to the back reef.
Communities solely on the windward side (East), while rare, were
not surveyed for focal research. Lastly, spatial distance between
villages, discrete natural borders, historical data, and pre-existing
governance research and relations, were considered. Coral reef
and market research was conducted in areas within and adjacent
to selected communities.
interactions in this social-ecological system. The fourth module
focused on the human health outcomes that arise from the socialecological system dynamics, linking together the ecological,
social, and economic modules.
By empirically researching each of these modules, we can
adequately assess the nutritional ecology of diet-related diseases
in Kiribati. Healthy marine ecosystems support healthy reefbased food systems, but do not guarantee positive health
outcomes by themselves. A range of governance and market
contexts mediate access to available food resources and are
therefore necessary considerations for understanding nutrition
security. These social and ecological domains are not, however,
independent. Degraded coral ecosystems can drive changes
in productive activities and market structures as communities
are pushed into more cash-based livelihoods, while processes
of globalization and urbanization can drive overutilization of
marine resources. Such feedback processes can create a “socialecological trap” that likely corresponds with differential nutrition
outcomes (5). Notably, greater integration with global markets
and the prevalence of cash-based economies is associated with
higher consumption of highly processed, fatty, and sugary foods,
facilitating the nutrition transition. Our sampling of the above
four modules across a range of ecological health and market
integration will allow us to identify how these dynamics may lead
to different health outcomes.
Training, Recruitment, and Enrollment
KNSO in collaboration with SPC, conducted a national census
in 2018 prior to the HIES, and, to the best of their knowledge,
documented every person in Kiribati (Figure 2). Using this
census as the sampling frame, and covering 21 of the total 23
inhabited islands of Kiribati, 182 clusters and 2,180 households
were randomly sampled using probabilistic two-stage selection
process for administering the HIES. The primary sampling unit
(enumeration area) was based on probability proportion to size
within each strata (South Tarawa, Northern, Central, Southern,
and Line Islands) and households within selected enumeration
areas were randomly selected. A total of 182 enumeration areas
were selected in total (50 in South Tarawa, 33 in Northern,
25 in Central, 40 in Southern and 33 in Line Islands). Within
each selected enumeration area, 18 households were randomly
selected-−12 were targeted for interview with the other 6 selected
as replacement households in case of non-response—using
randomized steps to select individual households. A response rate
of 100 percent was achieved, which included 12,481 individuals
(4,287 in South Tarawa, 2,094 in Northern, 1,430 in Central, 2,397
in Southern and 2,273 in Line Islands).
The HIES enumerators were split into five teams to cover all
targeted households across all of the surveyed islands. These five
teams would work in parallel over the course of 1 year (May
2019–March 2020) to complete the entire sample, distributed
across 21 islands in both the Gilbert and Line Island groups
(Table 1). The HIES enumerator teams were all I-Kiribati citizens
(predominantly women), recruited by KNSO and trained by
experts from SPC.
Prior to the beginning of the study, CG, WK, and JA traveled
to South Tarawa to train MHMS nurses from every island
in Kiribati to assist with the Integrated HIES health module
research (Figure 2), particularly the measurement of hemoglobin
and anthropometry. Five additional nurses were trained more
comprehensively to conduct the focal clinical health research
that took place in the aforementioned 10 islands. This training
included specific protocols to ensure inter-nurse reliability for
anthropometric measurements and detailed survey protocols to
ask questions and enter information onto tablets. Additionally,
JGE separately conducted training with four MFMRD Fisheries
Officers in South Tarawa prior to the commencement of the
ecological evaluation of coral reef health fieldwork. These field
Study Locations
Of the 21 islands that administered the HIES, we selected 10
islands to conduct the Integrated HIES, our focal research on
social-ecological dynamics of coral reef-based food systems.
We constrained our selection to only include islands whose
geomorphology comprised a low-lying coral atoll with a ringshaped coral rim partially enclosing a lagoon. Following that
inclusion criteria to standardize our observations, islands were
selected to represent a gradient of human pressure, coral reef
health, governance, and market integration. Specifically, in order
of prioritization: human population density, I-Kiribati national
priority [see (11)], geographic location within the island group,
spatial proximity to central markets and transit hubs, and
availability of historical data were used as criteria for selection.
Prior to finalizing the selection, a working group consisting
of the Kiribati National Statistics Office (KNSO), Ministry of
Health and Medical Services (MHMS), Ministry of Fisheries and
Marine Resources Development (MFMRD), Pacific Community
(SPC), American University (AU), Harvard T.H. Chan School of
Public Health (HSPH), University of California Santa Barbara
(UCSB), and University of California Santa Cruz (UCSC)
met to discuss scheduling, transport, logistics, and budgetary
restrictions. The final 10 islands were chosen (North to South)
in both the Gilbert Islands (Butaritari, Abaiang, North Tarawa,
South Tarawa, Abemama, Tabiteuea North, Tabiteuea South, and
Onotoa) and the Line Islands (Tabuaeran and Kiritimati).
Within these 10 islands selected for focal research, three
villages on each island were selected for human health and
ecological research (a total of 30 villages). The three villages
from each island were also selected to represent a gradient of
human population size and market integration. Villages that
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FIGURE 2 | Consort figure detailing integrated study components.
procedure occurred the following morning when the nurse would
arrive before breakfast to collect a signature for the informed
consent document, conduct a brief survey, and to collect fasted
biological samples. If a subject did not show up, it was assumed
that the individual did not consent to the research. Surveys lasted
∼15 min per person.
assistants learned the field, lab, and computing skills that were
required to conduct sampling. Upon arrival to each island,
the research team hosted capacity building meetings with the
Island Council. The workshops covered (1) the project’s research
objectives, schedule, data collection and future reporting, and
(2) the Island Council’s research goals and aims, governance,
fisheries objectives, historical information about the island, and
areas of specific importance or interest, including any known
ciguatera hotspots.
Of the 2,180 targeted households, we recruited 326 households
into the focal clinical health research. Persons of both sexes
and all ages were recruited into the research study, for a total
of 1,305 individuals (Figure 2). There was no screening based
on race or ethnicity. Households were defined as regularly
cohabitating groups of individuals who pool resources and share
meals. Subjects were offered no compensation for participating in
interviews, or for providing clinical samples. However, subjects
did receive the benefit of knowing the results of their pointof-care health tests. Individuals were recruited with a two-stage
opt-out procedure. On the evening before the research would
take place, a HIES enumerator and a nurse would visit the
household selected by randomization. During that visit, the HIES
enumerator would explain their research and the nurse would
explain the health research, and provide them with the informed
consent documents to review. The second stage of the opt-out
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Data Collection
Human Subjects Survey Data
Household Income and Expenditure Survey
The face-to-face survey, broken up into 40 rounds of collection,
was implemented over a period of 10-months (May 2019–March
2020) in order to capture seasonal fluctuations in consumption,
production and income. In addition to staff from KNSO, a
total of 10 interviewers and 5 supervisors—divided into 5
teams—were employed to implement the survey. The survey
questionnaire was developed in English using the World Bank
Survey Solutions Computer Assisted Personal Interview (CAPI)
software. The HIES questionnaire was divided into a series of
modules (Supplementary Table S1).
Beyond the household-level food recall, there was also
a module including a semi-quantitative food frequency
questionnaire, where individual respondents within households
were asked about the frequency of their consumption of 79 foods.
They were also asked an open-ended question about whether
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TABLE 1 | Study locations for the cross-sectional study in Kiribati with hypothesized reef health and market integration.
Popa
Island name
Island group
Strata
Community
name
Number of HH
(n sampled)b
Butaritari
Gilbert
Northern
Tabonuea
235
12
55
High
Low
Butaritari
Gilbert
Northern
Kuma
310
12
57
High
Medium
High
Number of Ind.
(n sampled)b
Rank reef
health
Rank market
integration
Butaritari
Gilbert
Northern
Ukiangang
655
24
133
High
Abaiang
Gilbert
Northern
Taburao
142
12
69
Med
Low
Abaiang
Gilbert
Northern
Tanimaiaki
312
12
53
Med
Medium
High
Abaiang
Gilbert
Northern
Tuarabu
548
12
70
Med
North Tarawa
Gilbert
Central
Tearinibai
441
12
59
Low
Low
North Tarawa
Gilbert
Central
Nooto
816
12
64
Low
Medium
High
North Tarawa
Gilbert
Central
Buota
1,647
24
138
Low
South Tarawa
Gilbert
Central
Nanikai
1,257
12
77
Low
Low
South Tarawa
Gilbert
Central
Bikenibeu
7,547
72
539
Low
Medium
South Tarawa
Gilbert
Central
Betio
18,565
168
1,273
Low
High
Abemama
Gilbert
Central
Tanimainiku
133
12
54
Med
Low
Abemama
Gilbert
Central
Tebanga
210
24
88
Med
Medium
Abemama
Gilbert
Central
Tabiang
618
24
98
Med
High
North Tabiteuea
Gilbert
Southern
Tauma
223
12
66
Med
Low
North Tabiteuea
Gilbert
Southern
Buota
436
12
71
Med
Medium
High
North Tabiteuea
Gilbert
Southern
Utiroa
774
24
118
Med
South Tabiteuea
Gilbert
Southern
Katabanga
82
12
76
High
Low
South Tabiteuea
Gilbert
Southern
Tewai
295
12
64
High
Medium
High
South Tabiteuea
Gilbert
Southern
Buariki
482
12
94
High
Onotoa
Gilbert
Southern
Buariki
208
12
55
High
Low
Onotoa
Gilbert
Southern
Aiaki
197
12
48
High
Medium
Onotoa
Gilbert
Southern
Temao
220
12
58
High
High
Tabuaeran
Line
Northern
Aramari
235
24
141
Med
Low
Tabuaeran
Line
Northern
Tereitannano
184
12
55
Med
Medium
High
Tabuaeran
Line
Northern
Tereitaki
370
12
62
Med
Kiritimati
Line
Central
Poland
404
24
161
Low
Low
Kiritimati
Line
Central
Banana
1,469
60
314
Low
Medium
Kiritimati
Line
Central
Tabwakea
3,573
96
584
Low
High
a Kiribati
2020 census (https://kiribati.popgis.spc.int/).
of households (HH), and individuals (IND) recruited on each island.
b Number
to a range of public services, such as the nearest hospital,
bank, and market. It also collected information about available
transportation options. The fourth section asked about migratory
work opportunities. The fifth section focused on fisheries assets,
commonly targeted and consumed aquatic resources, recent
changes in fisheries, including identification of recent natural
hazards and coral bleaching events, and documentation of rules
and customs related to fisheries. The sixth section detailed the
availability of physical infrastructure, such as sewage and waste
disposal. The final section focused on broad changes experienced
in the village within the past 10 years.
Of the 147 villages in Kiribati, the HIES was implemented in
111 and it was intended that one VRS would be conducted in
each village (i.e., VRS target was one interview to be conducted
in 111 different villages). In total, 109 villages were included in
the VRS with 111 interviews being completed (i.e., some villages
were interviewed more than once). The VRS questionnaire was
they consumed any additional foods from five categories:
cereals, seafood, fruit, vegetables, and snacks. These data were
collected from all individuals aged 12 and older residing in
households selected for the clinical health component of the
research. Further information on the HIES, including the survey
document, is publicly available (50).
Village Resource Survey
The Village Resource Survey comprised a maximum of 164
questions that provided context for the resources available
within the village, recent environmental history, access to fishery
benefits, and formal and informal rules around fishing and
gleaning activities. The survey had seven sections. The first
section detailed the characteristics of the interviewees, who were
selected based on key informant criteria. The second section
focused on property ownership and transfers. The third section
included a series of questions about the proximity of the village
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methylmercury contamination. Blood pressure, glucose, anemia,
and diabetes results were provided at point-of-care, with referrals
to local clinics or to the main hospitals as required. Filter papers
were stored at −3◦ C in cool boxes until they could be stored
for longer periods of time at the primary medical laboratory
in South Tarawa at −18◦ C. In order to collect whole blood for
gene expression profiling, we used a 23-gauge lancet to prick
the thumb of our participants. Nurses collected ∼10–15 drops of
blood (∼150 yl) in 1.5 yl cryotubes. The blood was stored in 500yl
of 2x DNA/RNA shield (zymo cat # R1200). These samples were
also stored at 4◦ C for up to a week and stored at −20◦ C thereafter.
administered to village authorities. Respondents included elected
village leaders (51), unimane/unaine (elders; 41), teachers (1),
pastors (2), and others (5). The data were collected via interview
of the HIES team supervisors using Survey Solutions Software.
Clinical Health Survey and Biological Sample Collection
The clinical health survey was conducted on a tablet using
software from the Dharma Platform of BAO Systems. These
questions were meant to complement the socio-economic,
demographic, and health questions that were included—as
standard—in the HIES. These questions focused on food taste
preferences and health and vaccination histories. Targeted
questions for reproductive-aged women included information on
pregnancy, lactation, menarche, menopause, and birth control.
The survey itself lasted only 10 min per individual. The survey,
all physical health measurements, and all biological sample
collection was conducted by one of five licensed nurses, who
were employed by MHMS, overseen by HM and ET, and trained
by CG, WK, and JA on specific research protocols. Because of
internet and data syncing issues with the Dharma Platform, we
lost a substantial amount of survey data.
Ecological Survey Data
To examine coral reef health we conducted ecological surveys
across three distinct habitats: shallow outer fringing reefs or
fore reefs (FR), lagoon reef (LR) pinnacles composed of reefbuilding corals, and subtidal soft sediment back reefs (BR). In
addition to the primary FR, LR, and BR sites within each of
the three habitat types, respectively, two additional sub-habitats
were assessed using different methods: deeper fore reefs were
surveyed by manta tows (MT) and nearshore low-tide exposed
soft sediment back reefs were surveyed by soft-infaunal quadrats
(SIQ). The location of sites within each habitat type were selected
randomly to be adjacent to the focal communities and >1 km
apart, where possible. For each island we designated 6 FR and 3
MT sites on the fore reef, 6 LR sites within the central lagoon, and
6 BR and 3 SIQ sites on the back reef (Figure 2). Selected sites
within each survey type were consistent in depth, relief, aspect,
and habitat structure. A subset of these surveys (3 FR, 3 LR, 3
BR, and 3 SIQ sites were randomly selected) included additional
research on water quality.
Anthropometric Measures, Clinical Nutrition, and
Disease Assessment
An I-Kiribati enumerator, as part of the HIES survey,
recorded the following anthropometric measurements (Table 2):
height/length and weight (all individuals); mid-upper arm
circumference (children 5 years of age and under); and cranial
circumference (children 2 years of age and under) using
standardized WHO protocols (52). Additionally, a fingerprick
was administered to all individuals <50 years of age, and
hemoglobin and hematocrit measures collected through the use
of a Hemochroma Plus device from Immunostics, Inc.
During the comprehensive clinical health survey that was
administered on 10 islands, an I-Kiribati nurse collected a
variety of measures and biological samples. Blood pressure was
measured for all individuals over 12 years of age using an
OMRON 10 series monitor. Measurements were taken after
at least 10 min of sitting, and ensuring that individuals were
as relaxed as possible. Subjects provided a maximum of three
finger pricks of blood, using one 23-gauge lancet and two 30gauge disposable lancets. Based on a subject’s age, he/she received
a different set of tests (Table 2). Using the two pricks with
the 30-gauge lancets, the capillary whole blood was used to
source samples for analyzing: (i) glucose levels with GenUltimate
Blood Glucose Test Strips for use with the One Touch Ultra
meter, (ii) total cholesterol, HDL cholesterol, and triglycerides
using the CardioChek Plus Analyzer from PTS Diagnostics;
(iii) hemoglobin A1c (a measure of diabetes) through the use
of a A1cNow+ device from PTS Diagnostics; (iv) blood cell
count through blood preserved on microscope slides; and (v)
fatty acid profiles through OmegaQuant filter paper treated
with HUFASaveTM (53). Additionally, dried blood spots were
collected on Whatman filter paper FTA cards (2 spots per
individual) for DNA extraction. Fingernails were also collected
from each individual enrolled in the clinical health study, with the
use of standard nail clippers, to assess the status of mercury and
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Ecological Community Surveys
A team of ecologists (JGE, KKB, and ATeki) conducted
marine community surveys to assess the species assemblage and
functional health of I-Kiribati coral reefs. All diurnal fish species,
non-cryptic invertebrates and the associated benthic habitats
were quantified across the FR, LR, and BR sites by free-divers
between 08:00 and 17:00 h. Observers were kept consistent to
limit observer bias. For each site, three replicate 50 m transects
were laid out using the belt transect method (n = 18 transects per
habitat, per island; method described further in (24)) with >10 m
spacing between transects. Transect placement was determined
by habitat structure, depth (2–4 m), and heading.
Fish Surveys
Underwater visual census (UVC) was used to characterize
the diurnal fish community assemblage. In order to avoid
preferentially recording highly mobile and more bolder fish
species and to limit diver effects (54), the fish observer (JGE)
laid out the transect tape during the first “swim out” while
simultaneously recording, identifying, sizing (nearest cm), and
sexing all fish with a total length >10 cm across a survey width
of 4 m (50 × 4 m benthic area per transect). On the second pass,
less mobile, cryptic, small-bodied, and site-attached species were
targeted with a more detailed examination of crevices across a
swath of 2 m (50 × 2 m benthic area per transect). All individuals
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TABLE 2 | Description of all survey data and instruments.
Oceanography and
microbiology assessment
Details
Sites
Dietary intake
24-h and 1 week food recalls
All
Market dynamics
Product availability indicates whether the product is available all of the time, a couple days
per week, a couple days per month, or seasonally
Village-Level
Price represents the price of the item at the time of the survey
Units indicate the units in which the item is sold in standard units (e.g., pounds, kilograms,
etc.) and nonstandard units (e.g., box, can, basket, etc.). The weight of items sold in
nonstandard units were recorded for calculating weight standardization factors
Socio-Economic status
(HIES)
Household income and expenditure survey (see Supplementary Table S1)
Head of household, or other qualified
respondent
VRS
Respondent Characteristics & Land Status—Key informant characteristics and
perspective on key village features like leadership, participation, land tenure
Community key informants
Transportation—Key informant perspective on transportation to key services within and
beyond the village
Community key informants
Industry—Key informant perspective on labor and occupations
Community key informants
Fisheries—Key informant perspective on village trends in seafood catch, sale, and
consumption, and comparisons to recent past and potential future
Community key informants
Physical Infrastructure—Key informant perspective on infrastructure and services
Community key informants
History & Development—Key informant perspective on comparisons between current
village indicators and historical context
Community key informants
Relative abundance of fishers by fishing method; maximum number (maxN) framework
using line of sight estimates
Island-wide
Clinical assessment
Details
Age group targeted
Anthropometry
Height/length
All
Weight
All
Mid-Upper arm circumference
Children 5 and under
Cranial circumference
Children 2 and under
Blood pressure
Measures systolic and diastolic blood pressure
Adults 12 and older
Glucose
Measures fasted circulating glucose
All individuals 12 and older
Metabolic disease via
CardioCheck
Measures fasted total cholesterol, HDL cholesterol, and triglycerides
All individuals 12 and older
Fishing effort field surveys
Calculates LDL, TC/HDL ratio, LDL/HDL ratio, and non-HDL cholesterol
Anemia
Hemoglobin and hematocrit
Diabetes
Measures hemoglobin A1c
All individuals <50 years
All individuals 12 and older
Fatty acid profiles
Analysis of dried blood cells by OmegaQuant. Provides readings of 23 different fatty acid
profiles to understand contribution of seafood to nutrition
Male and female head of household and
their oldest child
Mercury
Fingernail analysis for elemental mercury and methylmercury
All
Genetic markers
Evaluating genetic markers of physiological stress to better understand link between diet,
anthropometry, and metabolic disease
All individuals 3 or older
Blood cell count
Evaluated from blood on microscope slides
All
Ecological surveys
Details
Sites
Marine community surveys
All diurnal fish—underwater visual census; belt transects
FR, LR, BR
Highly mobile, rare, and flighty fish—underwater visual census; manta tows
MT
Infaunal surveys
Oceanography and
microbiology assessment
Water samples
All mobile and sessile invertebrates—underwater visual census; belt transects
FR, LR, BR
Large-Bodied targeted invertebrates—underwater visual census; manta tows
MT
Benthic habitat, relief, and complexity—uniform point contact; belt transects
FR, LR, BR
All mobile, sessile, and infaunal invertebrates—sediment harvesting; soft infaunal quadrats
and belt transects
SIQ
Benthic habitat, relief, and complexity– sediment harvesting; soft infaunal quadrats and
belt transects
SIQ
Details
Sites
Salinity—salinity tester
FR, LR, BR, SIQ
Conductivity—handheld conductivity meter
FR, LR, BR, SIQ
Temperature—refractometer
FR, LR, BR, SIQ
(Continued)
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TABLE 2 | Continued
Oceanography and
microbiology assessment
Details
Sites
Chlorophyll A—filtered by glass micron membrane filter paper, stored, and preserved
FR, LR, BR, SIQ
Nitrogen, Phosphorous, KH, Calcium—non-laboratory grade chemical
FR, LR, BR, SIQ
Diatom collection—filtered by glass micron membrane filter paper, stored and preserved
FR, LR, BR, SIQ
Microbiological samples—filtered by glass micron membrane filter paper, stored, and
preserved
FR, LR, BR, SIQ
Marine contaminants and
toxicology
Details
Sites
Heavy metal analysis
Macroalgae—Halimeda opuntia as a bioindicator of heavy metals
FR, LR
Fish—liver and muscle tissue from groupers (Serranidae), snappers (Lutjanidae), parrotfish
(Scaridae), and surgeonfish (Acanthuridae)
Island-wide; northern and southern
sectors
Turf algae—microalgal community samples to assess presence and concentration of
settled ciguatoxic dinoflagellates
FR, LR
Fish—liver and muscle tissue from groupers (Serranidae), snappers (Lutjanidae), parrotfish
(Scaridae), and surgeonfish (Acanthuridae)
Island-wide; northern and southern
sectors
Ciguatera analysis
Ecological habitats and sites: FR, fore reef; LR, lagoon reef; BR, back reefs; SIQ, soft-infaunal quadrats; and MT, manta tow.
a mobile invertebrate was landed on an adjacent point was
used), non-biological substrate (e.g., sand coarseness, rubble,
boulder), and corals [using definitions from (55)]. Low lying and
unidentifiable masses of tightly packed turf-forming filamentous
algae were recorded as turf algae [defined by Hay (56)]. All
macroalgae and corals were recorded to species or lowest
recognizable taxon by a consistent observer [KKB; using Kelley
(57)]. For crustose coralline algae (CCA), encrusting calcareous
algae, turf, or hard corals, growth form was classified as:
branching, tabulate, digitate, plating, massive, submassive, and
encrusting. When a live coral was landed on, the health of
each colony was additionally assessed by recording percent
bleached, presence and type of disease, and/or percent mortality
when present. Bleaching scores were based on the 6-point color
saturation scale on the CoralWatch Coral Health Chart in situ
to minimize subjective assessment of bleaching state (58, 59). If
bleaching was present, the coral was additionally characterized as
either stressed or bleached and percent mortality of total coral
structure was recorded.
In addition to point cover, the benthic observer recorded
relief (n = 50) and structural complexity (n = 50) for each
point. The change in vertical height between the shallowest
and deepest substrate point within a 25 cm² box was measured
and recorded as relief. Relief was binned by depth: (1) 0–
10 cm, (2) 10 cm−0.5 m, (3) 0.5–1.0 m, (4) 1.0–2.0 m, (5) 2.0–
3.0 m, and (6) >3.0 m. Complexity characterized the porosity
of the reef structure. For this study, an exponential scale
of 1–>10 was used: (1) 1, (2) 2–3, (3) 4–6, (4) 7–10,
and (5) >10. Similar to relief, complexity measurements
were considered by vertical height, however, unlike relief
measurements, complexity measurements were confined to the
vertical plane of that specific point (i.e., not within a 25
cm² box). For example, a point on the absolute bottom was
scored a (1) where a highly complex coral, such as Acropora
with >10 branches that crosses the vertical plane, was scored
a (5).
with a total length ≤10 cm were recorded, identified to the lowest
recognizable taxon, sized (nearest cm), and sexed (when possible)
as the observer more permanently fixed the transect. All fishes
were recorded, including individuals in the water column within
the defined benthic area (i.e., three dimensional surveys). When
large schools or shoals of fish were present, species were binned
by size class.
Invertebrate Surveys
After the completion of the UVC of fishes, a second
observer (ATeki) entered the water to quantify the invertebrate
composition and density along the fixed transects. For the
assessment of all mobile and sessile invertebrates, a swath
of 2 m was used (50 × 2 m benthic area per transect). All
species were recorded to the lowest recognizable taxon if
>50% of the individuals’ body was inside the swath. To
limit observer bias, “percent effort” was standardized. This
included time spent searching, team assistance, conditions (i.e.,
visibility, surge, and swell), and the lack of additional visual
tools (i.e., no underwater flashlight). In the instance of an
overabundance of a particular organism a sub-sampling method
was used in order to maintain percent effort. Sub-sampling
requirements were met when >50 individuals of a species
were recorded within one of the two 25 × 2 m transect
sections (0–25, 25–50 m). When this occurred, the observer
recorded the distance surveyed (in cm) and total count to
extrapolate the density out for the remaining distance within
that section.
Benthic Surveys
A benthic habitat assessment was conducted using a uniform
point contact (UPC) method along the fixed transect (50 m).
At each meter mark the observer recorded the identity of
the primary space-holding organism, excluding epiphytes, or
substrate beneath each point (n = 50). UPC cover categories
consisted of macroalgae, turf, seagrass, sessile invertebrates (if
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Manta Tow Surveys
Fishing Effort Field Surveys
Fine-resolution reef community surveys using the belt transect
method can occasionally underestimate rare species, largebodied individuals, and highly mobile or flighty species (54). The
manta tow technique, where a diver on breath-hold is towed
behind a small boat, is a method that has been adapted to census
these species and supplement belt transects. A primary advantage
of the technique is that it enables an observer to census species
of interest over large areas of reef benthos at speeds far greater
than a free-swimming diver. We conducted surveys at 3 manta
tow (MT) sites per island across a deeper aspect of the fore reef
to account for underestimation of rare, large, and flighty species.
Each MT site was established adjacent to a FR site, but was
conducted at a deeper depth (6 m) and on a different day to limit
observer bias (including boating disturbance). MT sites were
additionally selected to have consistent reef substrate (via satellite
imagery) and large channels or sand patches were avoided. At
each site 6,300 m transects with a swath width of 10 m were
surveyed (18 km² observed per site) with >30 m spacing between
transects. The tows were conducted by a consistent observer
(JGE) at a constant heading and depth (±1 m due to tidal swings),
in visibility >10 m, and at 3–4 km/h. A GPS was used to track
speed, distance, and heading. Fish and invertebrate species of
interest were recorded to the lowest taxonomic resolution, sized,
and sexed.
To supplement the HIES and VRS fishing pressure estimates,
in situ fishing effort surveys were conducted for all 10 focal
islands. While the ecological field research was being conducted,
observers (JGE, KKB, ATeki, and I-Kiribati boat drivers) visually
quantified the amount of (1) motorboats, (2) paddle canoes (waa
n oo), (3) sail canoes (waa n ieie), (4) shore-based net fishers, (5)
shore-based spear fishers, (6) shore-based hook and line fishers,
(7) gleaners, and (8) other efforts that were actively fishing and/or
transiting to, between or after a confirmed fishing effort. The
surveys were conducted using the maximum number (MaxN)
framework to estimate relative abundance and were recorded
twice daily; a.m. 8:00–12:59, and p.m. 13:00–18:00. Within the
recording periods, all observers actively observed fishing effort
within line of sight. MaxN is a commonly used method of
estimating maximum relative abundance using video recordings
or line of sight estimates when absolute observations are difficult
to obtain (61). Thus, MaxN is a conservative method where the
maximum number of samples observed at any one given time
throughout the entirety of a distinct trial period is recorded (62).
The method was designed to avoid the recurring counting of
individuals that enter a field of view within a trial (63).
When a potential fishing effort was observed by line of
sight during a trial period the observers watched for fishing
behavior, fishing evidence and discussed the boats intentions
with the local boat driver. A effort was not recorded when
the observers were not certain, with reasonable doubt, that the
effort was fishing based. When the method was not possible
to decipher it was recorded as fishing other. However, most
fishing effort was obvious, routine and verbally confirmed with
the fishers when catch was observed. Influencing factors, such as
the day of the week (limited fishing on Sunday), weather, wind,
and tide, were recorded. Lastly, observer distance was noted
as: a shore observation, lagoon near (associated village from
departure/arrival location), lagoon far (outside the study sites
for that village), leeward fore reef, windward fore reef or equal
distance, and other to account for spatial differences in effort.
Infaunal Surveys
While large-bodied reef-based invertebrates account for most of
the I-Kiribati subsistence invertebrate catch (e.g., Tridacna spp.),
a portion of fishing effort occurs on soft sediment habitat adjacent
to the communities (7). Shellfish gathering, or gleaning, can
fulfill nutritional needs when faced with fluctuations and seasonal
inequalities in the availability of other resources. In order to
quantitatively assess the abundance and diversity of species
targeted by gleaning (animals that burrow and live beneath the
substrate; e.g., the ark shell Anadara maculosa or te bun clams
and Trochus spp.) we conducted soft infaunal quadrats (SIQ) on
the soft sediment back reefs in areas exposed during low-tide
[see Pakoa et al. (60) for more detailed methods]. SIQ sites were
established 100–300 m inshore of the BR sites below the meanhigh tide mark. Community assessments were made across a
40 m transect, laid parallel to shore, and replicated 3 times with
>10 m spacing between transects. Observers randomly placed
4 25 cm² quadrats within a 2 m swath along the transect for
each 5 m segment (n = 32 per transect) and recorded the
relief, complexity, substrate (mud, sand, rubble, etc.), and cover
(seagrass, algae, sponges, epiphytes, etc.), when present. The
observer then excavated, using traditional I-Kiribati hand and
spoon harvesting methods (14), all sediment and organisms
down to approximately 10 cm. The composition of the sediment
and all visually identifiable species with >50% of the individuals’
body inside the quadrat was recorded. During sediment sorting,
“percent effort” (as described above) was not kept constant due
to inconsistencies in the sediment. Instead, effort was considered
complete when observers were 100% confident that all infaunal
species within the sampling area were quantified.
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Oceanography and Microbiology Data
Oceanographic Measurements
To complement the ecological survey data and assess differences
in oceanographic variables across the biogeographical and
anthropogenic gradients, we collected 8 oceanographic
measurements at 3 FR, 3 LR, 3 BR, and 3 SIQ sites per
island. At each water sampling site, we measured (1) salinity, (2)
conductivity, and (3) temperature using a handheld conductivity
meter (YSI Model 30), salinity tester (Hach Pocket Pro) and
a refractometer (Agriculture Solutions). All devices were
calibrated prior to each measurement following the calibration
specifications sheet provided by the manufacturer. Additionally,
(4) chlorophyll A was sampled following the EPA Method 445.0
(64). Following EPA’s guidelines, ocean water was filtered using
a glass microfiber filter paper (Whatman 1823-025, 25 mm
diameter) and then stored in a petri dish, wrapped in aluminum
foil to prevent light damage, and frozen at −80◦ C. Lastly, (5)
nitrogen, (6) alkalinity (KH), (7) calcium, and (8) phosphorus
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were tested in situ using a non-laboratory grade chemical kit for
approximation and preliminary qualitative analysis.
Turf Algae
In order to explore the presence of ciguatera in microalgal
communities, via benthic dinoflagellates of the genus
Gambierdiscus, we sampled turf algae from recently degraded
branching hard corals from the genus Acropora. Coral growth
form, turf morphology, height and density [following (71)],
temporal persistence and sediment load and composition (e.g.,
limited sand or silt) was standardized to the best of our ability
in situ when selecting coral colonies for sampling. Turf algae
was scraped, using a scalpel underwater, from the branch tips
(>1 cm) of each colony along the ecological community survey
transects with 2–5 m distance between coral colonies. Upon
surfacing, the sample was divided into two tubes for later
processing. DNA/RNA Shield was added to the first sample to
ensure a 9:1 ratio (shield to turf algae) depending on the amount
of turf collected. A 1% glutaraldehyde solution was added to
the second sample to allow for microscopic imaging of the cells
present. Turf algae samples were stored at −80◦ C.
Microbiological Samples
Three ocean water samples were collected at each site to assess
site-level microbiology. For the first sample, ocean water was
filtered through a glass micron membrane (Whatman 934-AH)
to a volume of 150 mL of ocean water (∼100 mL of cells) to
identify E. coli and giardia and assess the general bacteriology and
microbiology of the ocean water. The filter was transferred to a
sterile tube and DNA/RNA Shield (Zymo Research) was added
to ensure a 9:1 ratio (shield to ocean water cell solution). The
filter was submerged and agitated to preserve all cells present
on the filter surface. The above sampling and preservation
process was repeated for the second sample, but with 9 mL
of ocean water filtered through a glass micron membrane and
preserved with 1 mL of DNA/RNA Shield. The second sample
of higher ocean water volume supplements the first sample (of
standardized volume) to ensure sufficient cells for analysis were
captured if a site had a naturally low concentration of microbes.
The third ocean water sample was collected to preserve and
identify diatoms, dinoflagellates, and other primary producers.
Ocean water was filtered again using a glass micron membrane,
preserved in a 1% solution of 50% concentrated glutaraldehyde
and shaken aggressively. All tubes were stored at −80◦ C.
Reef Fish
Reef fish were collected from both northern and southern sectors
for each island to assess concentrations of heavy metals and
ciguatoxin across geographical scales. Survey locations were
selected during the initial capacity-building meetings with the
Island Council as the most common fishing grounds. Discussions
revolved around target catch (finfish) and reef habitat. To
standardize fishing grounds across islands, only leeward fore
reefs were sampled due to differences in island geomorphology
(particularly lagoon reefs). To engage the community and ensure
appropriate locations were sampled, we employed local fishers
to catch reef fish for the study. Species were selected based on
previously known I-Kiribati target species (14, 40). For each
sector, we sampled 3 fish from each of the 4 families (family;
example target species): groupers (Serranidae; Cephalopholis
argus, Epinephelus merra), snappers (Lutjanidae; Lutjanus bohar,
L. gibbus), parrotfish (Scaridae; Chlorurus sordidus, Scarus
frenatus), and surgeonfish (Acanthuridae; Ctenochaetus striatus,
Acanthurus nigricans). A total of at least 24 fish were sampled
per island. While specific target species were requested and
represented the majority of samples, other species from the
same genera were occasionally substituted. Additionally, we
opportunistically sampled other supplemental species, when
present. If a ciguatera hotspot was mentioned by the Island
Council (e.g., certain locations in Tabiteuea South), the area was
sampled in addition to the two fishing sectors. For all reef fish, a
geographic location within the sector was distinguished by having
the fisher select a location using satellite maps. Fish were kept
on ice or in a −17◦ C freezer, where possible, after catch, during
transit, and for storage prior to dissections.
For each fish, liver and muscle tissue samples were taken
for analysis of ciguatera and heavy metals, including mercury.
After standard and total length were measured, the entire liver
from the fish was removed and dissected into two 1 cm3 pieces.
One sample was submerged in DNA/RNA Shield and stored for
bacteriology, while the other standardized piece and remaining
liver, if any, were stored in separate zip lock bags for metal
analysis and future isotopic analysis, respectively. Scalpels were
Water Contaminants and Toxicants
Heavy metals and biotoxins in marine environments occur
naturally and are known to be concentrated near coastal human
populations due to nutrient pollution and runoff (65). Human
health risks may present in traditional communities that depend
on seafood as their primary animal-source food because of
the bioaccumulation of mercury or presence of biotoxins such
as ciguatera (42, 66). To link ecological, oceanographic, and
microbial indicators to human health, we examined both heavy
metals and ciguatera (known to be an issue in Kiribati). Algal
samples and fish were collected by free-divers and fishers,
respectively, across two of the three distinct reef habitats (3 LR
and 3 FR per island) where hard coral substrate was present.
Halimeda
Quantifying concentrations of heavy metals in marine
environments is challenging because trace metals (e.g., insoluble
sulfur) can interfere with salt matrix refraction (51). Standard
methods, such as inductively coupled plasma mass spectrometry
(ICP-MS) with ISO 17294-2 protocol measurements can be
used, but satisfactory performance results range from 41 to
86% with various metals (51). Instead, previous studies have
used macroalgae as a bioindicator of heavy metals in saltwater
(67–69). In the present study, Halimeda opuntia, a species of
green macroalgae, was selected as a bioindicator of metals to
establish a proxy of saltwater concentrations (70). Samples were
collected underwater (>50 g per sample) along the ecological
community survey transects with 2–5 m distance between
samples, dry-weighed in the field (Hochoice milligram scale),
and stored at −80◦ C.
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Intermediate Expenditure. All expenditure related to productive
activities and business were treated as intermediate expenditure
and were not included in the consumption aggregate.
sterilized between tissue dissections with 90% isopropyl alcohol
to avoid cross-contamination. The same procedure was followed
for the white muscle tissue samples resulting in 6 samples per
fish. Tissue samples were stored at −80◦ C. The animal study was
reviewed and approved by University of California Santa Barbara
IACUC.
Transfers. All transfers (e.g., cash gifts to other households,
or payments for fines) were excluded from the
consumption aggregate.
Data Analysis
Imputed Rent. The imputed rent component of the consumption
aggregate was computed for owner-occupied housing using
a predictive hedonic model, which was based on a range
of variables including tenure, physical dwelling characteristics
(number of rooms, building materials for walls, floor, roofing,
water connection, flush toilet, electricity grid connection, fuel
for cooking, and fuel for lighting) and location characteristics
(province, urban/rural) characteristics. The model was based
on rental expectations from the owner-occupying households
because only 5 of the 2,182 households were renting, a sample
deemed too small for an imputation model. For consistency
across renting and non-renting households, the imputed rent
from the model was used for all households, and actual rents were
not used in the consumption aggregate. Deductions were made
from the imputed rent for maintenance costs of owner occupiers.
The first module included general demographic and descriptive
analyses at the individual, household, village, and island levels.
These analyses utilized key basic indicators characteristic of HIES
surveys, including variables such as geographic location, age, sex,
poverty and food security status, and educational distributions,
and provided foundational context for subsequent research
modules on marine ecology (module 2), social, institutional, and
economic dynamics (module 3), and human health outcomes
(module 4). Further, these analyses provided key criteria for
comparisons between islands and villages within our study (e.g.,
along gradients of population density), and across time scales
(e.g., with past Kiribati HIES data).
Estimating Dietary and Nutrient Intake
The analytical methods applied to the 2019 HIES data are in
line with the latest international best practices and regional
guidance from the Pacific Statistics Methods Board (PSMB) on
the construction of consumption aggregates. The consumption
aggregate was finalized by the Statistics for Development Division
of SPC, with input from the Food and Agricultural Organization
of the United Nations and the World Bank.
Dietary Intake Food Frequency. Each of the 79 food groups
were coded into their respective frequencies of consumption
based on a provided serving size. All foods reported in “other”
categories were translated, coded, and incorporated during the
data cleaning and analysis stages. For each of the food groups,
participants reported the frequency with which they consumed
one serving based on the following options: (1) never/almost
never; (2) once per month; (3) once per week; (4) three times per
week; (5) daily; (6) more than daily; (7) more than three times
per day.
Construction of the Consumption Expenditure Aggregate
Food Consumption. The monetary value of food consumption
was attributed to the quantity consumed over the past 7 days
for each food consumed by each food acquisition source (cash,
own production, gifts, and exchange). The market survey was
used to convert quantities of consumption expenditure that
were reported in non-standard units of measurement to grams.
Whole food acquisition was converted into edible quantities
and nutrients using the Pacific Nutrient Database (72). Caloric
availability was derived using the Atwater equation where 1 gram
of protein = 4 calories, 1 gram of carbohydrate = 4 calories, 1
gram of fat = 9 calories, and 1 gram of pure alcohol = 7 calories
(72). Only food consumed by the household was included,
whether it was sourced from cash transactions, own-account
production, gifting, or through exchange.
Human Health Analyses
Clinical Health and Anthropometric Data Analyses
Anthropometric data were analyzed using standard WHO cutoffs
to assess nutritional status. Children under 5 were assessed
as underweight (weight-for-age z-score <-2), being stunted
[height-for-age z-score (HAZ) <-2], wasted (weight-for-height
z-score <-2) and overweight (weight-for-height z-score > 2)
based on the WHO Child Growth Standards (52). Mid-upper
arm circumference (MUAC) was used to assess severe acute
malnutrition in children based on a MUAC <11.5 cm in children
under 5, and moderate acute malnutrition based for a MUAC
≥ 11.5 cm and <12.5 cm. For children <24 months, a headcircumference-for-age z-score <-2 was classified as a case of
microcephaly. In children ages 5–19, overweight was classified
based on a body-mass-index-for-age z-score (BMIZ) > 1, and
obesity was classified as a BMIZ > 2. In adults ages 20 and above,
body mass index (BMI) was used to classify nutritional status in
the following way: underweight, BMI<18.5; 18.5–24.9, normal
weight; 25.0–29.9, overweight; 30.0–34.9, obesity class I; 35.0–
39.9, obesity class II; and >40, obesity class III. Observations were
considered to be outliers if their WAZ or HAZ were > |6| or their
head circumference z-score or WLZ were > |5|.
Non-durable (and Non-food) and Semi-durable Consumption.
The consumption of non-food non-durable and semi-durable
items was calculated as the annualized value of reported
transactions for individual and household expenditures. Outliers
were detected by product type and area in log-space using +/−2.5
× IQR and, where detected, locational medians were imputed.
Durables. Durables are items that are infrequently purchased by
the household and have a long life (>1-year). Consumption of
durables was estimated based on their use value.
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and CNV analysis will be performed using the Genome Studio
2.0 (Illumina Inc. SD, California). We will exclude participants
if (i) genotyping fails at more than 5% of SNPs, and/or (ii)
if their heterozygosity rate is >3 standard deviations from the
cohort mean. We will also exclude rare alleles (minor allele
frequency (MAF) <0.01) and those that are not in Hardy–
Weinberg Equilibrium (p < 1 × 10–6). LD will be calculated
using r2 implemented in PLINK (78) and removing one SNP of a
pair each time r2 > 0.6.
Two blood smears (Peripheral Smear) were collected for
each participant to calculate blood cell counts. Following
fixation, each slide was evaluated for differential white blood
cell count (WBC). This count was done manually using a
microscope and a cell counter for neutrophils, lymphocytes,
monocytes, eosinophils, and basophils. WBC percentages were
standardized for each WBC. Normal ranges in adults are:
neutrophils (55–70%), lymphocytes (20–40%), monocytes (2–
8%), eosinophils (1–4%), and basophils (0.5–1%) of total
white blood cells (79). We also evaluated each participant
for RBC irregularities (e.g., anisocytosis—indicative of anemia;
poikilocytosis and anisopoikilocytosis), the presence of abnormal
cells (e.g., presence of immature white blood cells such as blasts,
indicative of leukemia, or serious bone marrow disease) and
infectious agents. Note that a variety of diseases and conditions
can affect the relative number of WBC, and we primarily intend
to use variation in WBC as a covariate in downstream analysis
(e.g., blood gene expression profiling).
Anemia status was classified into non-anemia or mild,
moderate, or severe anemia based on hemoglobin levels (g/dL)
with respect to age and pregnancy status per the WHO
recommendations (73). In children 6–59 months of age, anemia
was classified as follows: mild, 10.0–10.9 g/dL; moderate, 7.0–9.9;
and severe, <7.0. In children 5–11 years of age: mild, 11.0–11.4
g/dL; moderate, 8.0–10.9; and severe, <8.0. In children ages 12–
14 and non-pregnant women over age 15: mild, 11.0–11.9 mg/dL;
moderate, 8.0–10.9; and severe, <8.0. In pregnant women: mild
anemia, 10.0–10.9 g/dL; moderate, 7.0–9.9; and severe, <7.0.
Lastly, men ages 15 and above were classified as having anemia as
follows: mild, 11.0–12.9 mg/dL; moderate, 8.0–10.9; and severe,
<8.0. Non-anemia was designated in the absence of anemia per
the classifications of each group.
Blood pressure was considered to be: normal if systolic <120
mmHg and diastolic <80 mmHg; elevated if systolic was ≥120
and ≤129 mmHg and diastolic <80 mmHg; Stage 1 hypertension
if systolic was ≥130 and ≤139 mmHg or diastolic was ≥80 and
≤89 mmHg; Stage 2 if systolic ≥140 and ≤180 mmHg or diastolic
≥90 mmHg; and Hypertensive Crisis if systolic > 180 mmHg
and/or diastolic >120 mmHg (74).
Metabolic syndrome, and its constituent measures, all
followed from American Heart Association guidance (75). In
individuals over age 12, fasting plasma glucose levels ≥180
mg/dL were considered hyperglycemic; 70–180 mg/dL normal,
and ≤70 mg/dL hypoglycemic. An individual was considered
to be pre-diabetic if their hemoglobin A1c (HbA1c) levels were
between 5.7 and 6.5%; diabetic if their HbA1c ≥ 6.5%; and
non-diabetic if their HbA1c < 5.7%. Cholesterol levels were
considered normal if total cholesterol <200 mg/dL, HDL >
40 mg/dL, and LDL < 130 mg/dL. Cholesterol levels were
considered at-risk if total cholesterol ≥200 or HDL ≤ 40
or LDL ≥ 130. Triglycerides were assessed as follows: <150
mg/dL as low-normal; ≥100 and <150 mg/dL as high-normal;
≥150 and <200 mg/dL as borderline hypertriglyceridemia; ≥
200 and <500 as moderate hypertriglyceridemia; and ≥500
mg/dL as severe hypertriglyceridemia. Note that the CardioChek
Plus cannot read triglyceride values below 50 mg/dL, therefore
neither triglyceride nor LDL cholesterol values were recorded for
these individuals. LDL cholesterol is estimated as a function of
triglyceride, HDL cholesterol, and total cholesterol levels using
the Friedewald Equation (LDL cholesterol = total cholesterol—
HDL cholesterol—triglycerides/5) (76).
Ecological Analysis
The second module featured marine ecological research on the
health and status of the coral reef system. To examine how
coral reef health influences human health, the ecological research
module focused not only on species with key functional roles, but
also on species and ecosystems significant to I-Kiribati fisheries,
food security, and cultural importance. Ten ecological indicators
(EI) across multiple dimensions were used to assess ecosystem
health, capture natural variation, and incorporate interactions
between species and the environment. Variability in the structural
composition and geomorphology of coral reef atolls, as described
above, constitutes distinct ecosystems, or habitats, with different
species compositions and oceanographic conditions. The back
reef, where SIQ infaunal survey data was collected, hosts a
different, but important, assemblage of species than those found
on the atoll’s lagoon or fore reefs. Thus, analysis was focused on
the status of different species assemblages across all habitat types.
We use (EI 1) abundance, (EI 2) richness, and (EI 3)
size structure data of frequently harvested and functionally
important fish and invertebrate species from the community
surveys as primary ecological indicators. For example, species
such as the humpback red snapper Lutjanus gibbus or green
humphead parrotfish Bolbometopon muricatum, respectively, can
offer insights into the relative health of the lagoon reefs or fore
reefs when using these three indicators. With the community
survey data, we then assigned fishes to (EI 4) broad trophic
categories and converted counts and total lengths to (EI 5)
biomass density using trophic classifications and length-weight
conversion compiled by the Ecosystem Science Division of
Fatty Acid Profiles
All OmegaQuant filter papers, treated with HUFASaveTM , were
sent to OmegaQuant laboratories for fatty acid analysis following
established protocols (53). Their analyses produce 24 fatty acid
profiles, including eicosapentaenoic acid (EPA), docosahexaenoic
acid (DHA), and an overall omega-3 index, which has been
associated with various forms of morbidity and mortality (53).
Genetic and Immunological Analyses
DNA was extracted from dried blood spots using Zymo QuickDNA extraction Kits. Participants will eventually be genotyped
using Illumina’s Infinium Global Screening Array v1.0 (GSA)
from Illumina (77), which includes 642,824 SNPs. Genotypic calls
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4) chlorophyll A was used to measure primary productivity
as an indicator of runoff. We coupled the chlorophyll A
data with nitrogen, alkalinity (KH), calcium and phosphorus
within the analysis to triangulate water quality due to the
biochemical properties of ocean water (unlike freshwater tests).
Due to the variability of ocean water composition, reported
concentrations may not always accurately represent long-term
values, particularly when comparing offshore and in-shore
environments (86, 87). Nitrogen (OI 5) measurements were
used to quantify excess bacterial decomposition in water,
particularly in locations close to shore (e.g., SIQ sites) and near
densely populated areas (highly developed communities). The
combination of (OI 6) calcium and (OI 7) KH highlighted
approximate levels of dissolved calcium present in the reefs, as
well as the stability of those calcium ions. KH was specifically
used to demonstrate the potential buffering capacity across
the study sites. Lastly, (OI 8) phosphorus was measured, as
an overabundance may signal a eutrophication event and the
potential for harmful algal blooms, which may be associated with
ciguatera outbreaks (88).
By using the 8 oceanographic measurements and historical
data on climate impacts (i.e., NOAA Coral Reef Watch: degree
heating weeks), we can produce maps of spatially explicit
climatic influences. Together, these variables provide a baseline
environmental gradient to evaluate anthropogenic impacts on
coral reefs. Eventually, we will evaluate these biophysical
drivers in conjunction with heavy metals, diatom species
identification, and ciguatoxin analysis to examine associations
with human health.
NOAA’s Pacific Islands Fisheries Science Center from FishBase
(80). We hypothesized that degraded and overfished reefs would
have lower biomass density of trophic groups targeted by
fishers, such as large predators. Fish biomass, coupled with
trophic structure, has been used globally as a primary way to
describe coral reef function. However, while trophic structure
depicts the entire systems’ connectivity of direct and indirect
feeding relationships, species within trophic groups operate in
different functional roles that influence the ecosystem’s health,
resilience, or resistance to impacts or shock. Thus, we further
assessed the health of the species assemblage and ecosystem
by examining (EI 6) the functional structure (81) and (EI 7)
overall biodiversity [measured by using functional structure and
species richness; see (82)]. For example, reefs that have great
biomass at intermediate consumer levels, which can be described
as “middle-drive” systems are functionally different from reefs
with trophic structures that appear top-heavy (80).
While the community, manta tow, and infaunal surveys
provided a way to evaluate the frequently harvested and
functionally important fish and invertebrate species, the benthic
surveys also contributed supplementary ecological indicators of
coral reef health. The transition from a coral-dominated reef
to a degraded, macroalgal-dominated reef is the most common
way to assess coral reef functional health when comprehensive
benthic data is available (83). Thus, the (EI 8) percent substrate
cover and proportion of scleractinian framework-building corals
vs. macroalgae and/or turf was used to determine the level
of degradation across sites and islands. Similar to EI 6 for
fishes, we then assessed the (EI 9) functional diversity of the
coral assemblage using the life history categories proposed in
Darling et al. (84): competitive, stress tolerant, generalist, or
weedy. The categorizations were developed and synthesized from
a trait-based approach with species characteristics of colony
morphology, growth, calcification and reproduction (https://
coraltraits.org). Analyzing the functional classifications of corals,
when assessed proportionally, can indicate the frequency and
intensity of thermal disturbances, anthropogenic impacts, and
together, the levels of historic degradation. Shifts in dominant
traits from competitive habitat specialists to weedy generalists
also can be attributed to the structural complexity of the habitat
(24). As coral reefs degrade, the cover of total live coral and
branching corals decreases and structural complexity is lost,
which decreases the resilience of coral reefs to disturbances (85).
Thus, because structural complexity is an integral component of
the coral reef ecosystem, (EI 10) the relief and complexity were
analyzed as the final benthic ecological indicator.
Water Contaminant and Toxicant Analysis
Metal Analysis Preparation
To prepare samples from Halimeda opuntia and fish for analysis,
they were removed from a deep freezer (−80◦ C), lyophilized
(MechaTech Systems, LyoDry Compact), and transferred
to sterile tubes (VWR Centrifuge Tube, 76204-404, Batch:
190717060 and 190609058). Samples were ground using a
metal spatula sterilized using 10% Hydrochloric acid (J.T.
Baker, Hydrochloric Acid 36.5–38.0%, Baker Instra-Analyzed
Reagent, 9530-33, Batch No: 000024173 diluted with deionized
water). Tissues were weighed for dry-weight before Thermo
Quant’X EDXRF (XRF) and mercury analysis (Mettler-Toledo
AG XPE205DR).
Total Mercury Analysis
Ground samples were analyzed at Harvard University for total
mercury concentration (T-Hg) on a direct mercury analyzer
(DMA) (NIC MA-3000 Mercury Analyzer and MA3 Win
software) following US EPA Method 7473 (US EPA 1998).
This process involves measurement by thermal decomposition,
reduction, amalgamation, and atomic absorption spectrometry.
A quality control and assurance series was run every 12 samples.
This series included the following: blanks (2), deionized water
purge (1), dry purge (1), Apple Leaves 1515 (1) (NIST Standard
Reference Material (SRM), US Department of Commerce
National Institute of Standards and Technology, Gaither, MD
20899), MESS-4 SRM (1) (Marine Sediment SRM, National
Oceanographic Analysis
In addition to the ten ecological indicators, oceanographic
indicators also can modify ecosystem health. Eight biophysical
drivers were considered to evaluate the quality of the ocean water
and further describe current reef conditions. We measured (OI 1)
salinity and (OI 2) conductivity to indicate the concentrations of
salt ions and dissolved solids in water, respectively. Temperature
data (OI 3), both current and historic, was used to monitor
current conditions, which can be a precursor to harmful algal
blooms and coral reef degradation. For in situ data, (OI
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Research Council Canada, Lot G 4169010, Serial CC 567765)
to verify recovery rates and sample integrity. Calibration curves
were set using R2 > 0.99 and SRM recovery was 87–102%
confirming the accuracy of measurements. Amalgamator and
catalyst tubes were replaced as needed due to excessive calcium
carbonate deposition from the tissues.
To prepare human fingernail samples, they were cleaned with
a 1% triton deionized (DI) water solution, sonicated for 30 min,
vortexed, and soaked for an additional 2 days (89). This process
of sonification and rinsing was repeated three more times,
including an acetone rinse, and nails were then freeze-dried
overnight. Total mercury (Hg) concentrations were measured
with a Nippon MA-3000 mercury analyzer (U.S. EPA 1998) along
with a certified reference material (European Reference Materials
(ERM-DB001), human hair).
Ciguatera Analysis
Reef fish samples (liver and white muscle tissue) and turf algal
samples were shipped to the National Oceanic and Atmospheric
Administration (NOAA) to analyze the presence of ciguatoxin
(CTX) using their fluorescent receptor binding assay protocol
(90). This process involves a fluorescence-based receptor binding
assay [RBA(F) ], based on competition binding between CTX
and fluorescent-labeled brevetoxin-2 with voltage-gated sodium
channel receptors. The analysis detects the presence or absence of
ciguatoxin, toxicity levels, and the percent binding equivalents.
Social, Institutional, and Economic Analyses
To examine how informal and formal governance structures
mediate access to reef fish and their resource benefits, the
governance research module combined data collected from
both the HIES and the VRS surveys. As a representative
sample of I-Kiribati households, the HIES provided standardized
quantitative data on: household knowledge of and adherence
to formal (e.g., Government of Kiribati) and informal (e.g.,
traditional, religious) fisheries rules and customs; inter- and
intra-household dynamics of reef fishing and reef food access;
prevalence and diversity of practices such as catch sharing
and gifting; and how individual households with various
characteristics utilize reef resources and access reef foods.
Additionally, as a key informant survey of local village
representatives, the VRS provided additional insights into: the
specific rights, rules, and decision-making procedures applicable
within a village; criteria for participation in various forms of
village and fishery institutions, capital and assets available within
the village or held in common, and historical context for the data
provided by households through the HIES.
To examine how markets and trade mediate access to reef fish
and their resource benefits, the market survey provided data on
product availability, frequency of availability and price by village.
We construct a product diversity score based on the market data
and pair this with VRS data on proximity and travel time to other
market centers. Together, these variables serve as an indicator
of the market integration with formal markets in each village.
We compare the prevalence of processed and high fat/high sugar
foods available in the formal markets to the local produce and
animal products sold within the village to measure the degree of
nutrition transition of the supply.
Heavy Metal Analysis
To test the concentration of heavy metals present, samples were
analyzed using inductively coupled plasma mass spectrometry
(Thermo Scientific, iCAP Q) following EPA Method 6020B (U.S.
EPA 2014). This process involves ∼100 mg of dried samples
digested at 95◦ C for 6 h using a 4 mL nitric acid and hydrogen
peroxide solution (3:1, respectively, J.T. Baker, Instra-Analyzed
Reagent, Batch No: 0000221802). Post digestion, samples were
diluted to 30 mL using deionized water and measured on ICPMS. Calibration of ICP-MS was conducted using Multi-Element
Solution 2 (Spex CertiPrep, USA). Average recovery rates for
calibration standards and trace metals in water SRM (NIST
1643f) analyzed as samples were generally in the range of 90–
110%, supporting measurement accuracy. These results allowed
for comparison of mercury values between two machines.
All samples were then tested for heavy metals using X-ray
Fluorescence, which is a faster analysis process.
We used a Thermo ARL Quant’X EDXRF (XRF; Thermo
Fisher Billerica, MA) for non-destructive analysis of a suite of
elements. The system was run for 30 min live time for each
sample with x-ray settings of 50 kVp and 1 mA using a silver
filter and anode. Samples were measured in 30 mm diameter,
polyethylene XRF sample cups with a 2.5 um mylar support
film. XRF was optimized for sampling over a 20 mm2 area
to a depth of approximately 0.5 cm. Samples would rotate
during measurement to ensure a full homogenous measure of
the cup and sample. XRF spectra was analyzed using in-house
peak fitting methods calibrated against standards with known
composition (89).
Ethics Approval and Consent to Participate
The HIES was implemented by the Kiribati National Statistics
Office in accordance to the 1974 Statistics Ordinance, which
assigns authority to the Republic Statistician to collect and
compile information relating to, among other areas, household
expenditure, health and fishing. For the clinical health research,
all households were recruited and enrolled, and each individual
consented or assented, following our IRB approved study
(Protocol #18-0967, Committee on the Use of Human Subjects,
Office of Human Research Administration at the Harvard T.H.
Chan School of Public Health). The study was also approved by
the Ministry of Health and Medical Services in Kiribati. All pointof-care health results (anemia, diabetes, hypertension, etc.) were
Water Microbiological Analyses
Water samples will be analyzed to explore the presence of
various human relevant diseases. DNA/RNA solutions can be
later used for extraction and DNA sequencing to screen for
bacteriology analysis which can detect cryptosporidium, fecal
coliforms, giardia, and general bacterial presence. We will
use a combination of 16S rRNA and shotgun metagenomics
sequencing to identify variations in community composition that
may correlate with adverse health outcomes.
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TABLE 3 | Demographic and disease status summary statistics of the enrolled HIES study populationa .
Overall
Gilbert
Line
High development
Low development
12,351
10,080
2,271
6,222
6,129
0–5 years
14.9
15.0
12.7
15.5
13.7
6–11 years
14.3
14.3
14.6
13.5
15.7
12–17 years
10.9
10.6
14.5
10.1
12.4
18–49 years
45.5
45.7
43.3
47.8
41.5
50+ years
14.4
14.4
14.9
13.0
16.8
Respondent is female (%)
49.3
49.5
46.2
49.6
48.7
% Pregnant, women ages 15–49
5.5
5.3
8.8
5.0
6.6
Mild
9.7
9.9
7.3
8.8
11.3
Moderate
9.5
9.7
6.1
9.1
10.2
Severe
1.7
1.8
0.6
1.3
2.4
Non-anemic
79.2
78.6
85.9
80.8
76.1
Mild
14.2
14.2
15.2
12.8
16.9
Moderate
17.3
16.9
21.9
13.9
23.7
Severe
2.7
2.8
1.3
1.1
5.9
Non-anemic
65.8
66.1
61.7
72.2
53.4
Moderate stunting
16.1
16.0
17.1
16.5
15.4
Severe stunting
7.5
7.2
10.7
6.9
8.6
Not stunted
76.5
76.8
72.2
76.7
76.0
n
Age group
Anemia status, women ages 15–49
Anemia status, children <5
Anthropometry, children <5
Stunted (%)
Wasted (%)
Moderate wasting
4.1
4.2
2.2
3.7
4.9
Severe wasting
2.8
2.9
1.2
2.9
2.5
Not wasted
93.1
92.9
96.6
93.4
92.7
Moderate underweight
7.1
7.1
6.4
7.3
6.6
Severe underweight
3.0
3.1
2.2
2.3
4.3
Not underweight
89.9
89.8
91.4
90.4
89.0
Underweight (%)
BMI of adults 18+
Underweight
0.9
0.9
0.6
0.7
1.2
Normal weight
20.4
20.6
18.1
18.1
24.5
Overweight
32.4
32.5
30.3
32.5
32.1
Obesity class I
26.2
26.1
27.9
27.0
24.9
Obesity class II
13.9
13.8
14.8
15.0
11.9
Obesity class III
6.3
6.1
8.2
6.8
5.4
a The
sample sizes for the variables in this table (due to missing data and data subsetting) are as follows: age group and sex = 1,351; pregnancy = 2,353; anemia status of women
15–50 = 2,429; anemia status of children < 5 = 1,407; anthropometry of children < 5 = 1,392; BMI of adults 18+ = 6,201. BMI, Body mass index. Child anthropometry excludes
suspected data errors with weight-for-age z-scores >6 or <-6; length/height-for-age z-scores >6 or <-6, or weight-for-length/height z-scores >5 or <-5 (a total of 71 children).
Moderate wasting/underweight/stunting is classified as a z-score <-2, and severe wasting/underweight/stunting is classified as a z-score <-3. Adult BMI was calculated as kg/m2 and
excluded for a BMI > 80, or a height <111.8 or >228.6 cm; or a weight <24.9 or >453.6 kg (a total of 56 adults). Anemia was calculated and categorized based on the WHO guidelines
accounting for age and pregnancy status (73).
environment of chronic overnutrition whereby individuals
are consuming too much dietary energy. There is a moderate
prevalence of anemia in both reproductive-aged women
(21.9%) and children under 5 years of age (34.2%). The
population is heavily left-skewed with more than 40% of
the population being <18 years of age, indicating rapid
population growth in this region. Laboratory analyses are still
in progress; baseline HIES point-of-care results are shown in
Table 3.
provided by our team’s health professionals to the study subjects
including access to free treatment and referrals to local clinics.
INTERIM RESULTS
We found a moderate prevalence of stunting (23.6%),
wasting (6.9%), and underweight (10.1%) throughout the
study population (Table 3). Yet, 78.8% of the population is
either overweight (32.4%) or obese (46.4%), indicating an
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Reef Fisheries and Human Nutrition
DISCUSSION
VRS and market components of the study. MS and AT led the
HIES implementation. KS led the social and governance research
modules. HB, PB, AS, ES, and CG led the heavy metal analyses.
HB, JE, and CG led the ciguatera study design. HM, RT, ET, and
KN led the local management of health staff and research sample
collection. KB, HB, and ATeki assisted with the ecology module
and WK assisted with the human health module. JK assisted
with the data collection infrastructure for the health research.
KG, SP, NN, MS and JM cleaned, coded, and analyzed data
collected from the research. CG, JE, JG, KS, MS, and HB drafted
the manuscript. All authors have edited and approved of the
final manuscript.
The main strength of this cross-sectional study is that the HIES
modules are nationally representative and include both sexes and
all ages of I-Kiribati society of the Gilbert and Line island groups.
Moreover, a subset of these islands (ten in total) became part
of what the Pacific Community is calling the Integrated HIES
that connects ecological and human health data collection to the
ongoing social, demographic, and economic data collection of
the HIES. The integrated HIES becomes a more powerful study
design to understand the underlying ecological drivers of social
and economic patterns that can lead to various human health
sequelae [e.g., (5)].
Our initial results paint an unfortunately typical picture
of health status in the Pacific with moderate prevalences of
undernutrition and anemia and an extremely high prevalence
of obesity. Furthermore, given the vulnerability of this region
to climate change, this population is characteristic of what is
termed a global syndemic connecting undernutrition, obesity,
and climate change (91). As this syndemic creates inherent
connections among climate, environment, and human health, it
is essential that the Integrated HIES continues to collect data and
monitor populations so that governments and policymakers can
learn and adapt to changing conditions.
The primary limitation of this study design is that we are
establishing a baseline for future work, and thus it does not yet
include longitudinal data. Future longitudinal data will allow
us to understand the ways in which changing environments,
and changing climates, may shape food systems and dietary
intake patterns, thus influencing health outcomes such as obesity,
hypertension, and diabetes.
FUNDING
We are grateful for the financial support of the National
Science Foundation (CNH 1826668), in-kind support
from the Dharma Platform of BAO Systems, and
the leveraged funding from the Pacific Community
(SPC) to collaborate with the Government of Kiribati
on their Household Income and Expenditure Survey
(HIES). MS was funded by the Australian Government
through Australian Center for International Agricultural
Research (FIS/2018/155).
ACKNOWLEDGMENTS
We would like to thank the following people: Tebwebweiti
Tikanibwebwe (MHMS), Tebano Bwabwa (MHMS),
Nantebwebwe Toabo (MHMS), Bwaturia Temaua (MHMS),
Baurina Kaburoro (MHMS), Tirite Irooti (MHMS), Regina Flood
(MHMS), Kiaman Raurenti (MHMS), Chris Holland (NOAA),
Mark Vandersea (NOAA), Aaron Specht (HSPH), Agnes Yeeting
(MFMRD), Tooreka Teemari (MFMRD), Max Peter (MFMRD),
Taratau Kirata (MFMRD), Toaea Teawatei (MFMRD), Tebatei
Kourabi (MFMRD), Karibanang Tamuera (MFMRD), Rateiti
Vaimalie (MFMRD), Marouea Rabwerei (MFMRD), Toga
Raikoti (SPC), Olivier Menaouer (SPC), Bertrand Buffiere (SPC),
Nathalie Troubat (FAO), and Tiriara Ikam (MFED).
ETHICS STATEMENT
The studies involving human participants were reviewed and
approved by Harvard T.H. Chan School of Public Health
Office of Regulatory Affairs and Research Compliance. Written
informed consent to participate in this study was provided by
the participants’ legal guardian/next of kin. The animal study
was reviewed and approved by University of California Santa
Barbara IACUC.
SUPPLEMENTARY MATERIAL
AUTHOR CONTRIBUTIONS
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fpubh.
2022.890381/full#supplementary-material
The study was designed by CG, JA, JE, JG, KS, MS, DM, KN, and
AT. CG, JA, and KN led the human health modules of the study.
JE led the ecology module of the study. MS, KS, and JG led the
Supplementary Table S1 | This table provides details on the type, frequency,
and measurements collected for each survey.
REFERENCES
health, fish and human welfare, economy and environment. Fish Fisher. (2016)
17:893–938. doi: 10.1111/faf.12152
3. Golden CD, Allison EH, Cheung WWL, Dey MM, Halpern BS, McCauley
DJ, et al. Nutrition: fall in fish catch threatens human health. Nature. (2016)
534:317–20. doi: 10.1038/534317a
4. Raiten DJ, Bremer AA. Exploring the nutritional ecology of
stunting: new approaches to an old problem. Nutrients. (2020)
12:371. doi: 10.3390/nu12020371
1. Golden CD, Koehn JZ, Shepon A, Passarelli S, Free CM, Viana
DF, et al. Aquatic foods to nourish nations. Nature. (2021)
598:315–20. doi: 10.1038/s41586-021-03917-1
2. Jennings S, Stentiford GD, Leocadio AM, Jeffery KR, Metcalfe JD, Katsiadaki
I, et al. Aquatic food security: insights into challenges and solutions from
an analysis of interactions between fisheries, aquaculture, food safety, human
Frontiers in Public Health | www.frontiersin.org
18
June 2022 | Volume 10 | Article 890381
Golden et al.
Reef Fisheries and Human Nutrition
27. Brewer TD, Andrew NL, Sharp MK, Thow AM, Kottage H, Jones S. A
Method for Cleaning Trade Data for Regional Analysis: The Pacific Food Trade
Database. Version 2.1. Pacific Community Working Paper. Noumea (2022).
28. World Bank. Kiribati- National Statistics. World Bank (2020). Available online
at: https://data.worldbank.org/indicator/SP.POP.TOTL?locations=KI
29. Thow AM, Snowdon W. The effect of trade and trade policy on diet and
health in the Pacific islands. In: Hawkes C, Blouin C, Henson S, Drager N,
Dube L, editors. Trade, Food, Diet, and Health: Perspectives and Policy Options.
Hoboken, NJ: Wiley-Blackwell (2009). 147–68.
30. World Bank. Kiribati- Urban Population. World Bank (2020). Available online
at: https://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS?locations=KI
31. FAO. FAOSTAT: Food and Agriculture Data. FAO (2020). Available online
at: http://www.fao.org/faostat/en/#data
32. Environmental Protection Agency. Mercury Emissions: The Global Context.
US EPA (2014). Available online at: https://www.epa.gov/internationalcooperation/mercury-emissions-global-context (accessed May 8, 2020).
33. Baishaw S, Edwards J, Daughtry B, Ross K. Mercury in seafood: mechanisms
of accumulation and consequences for consumer health. Rev Environ Health.
(2007) 22:91–114. doi: 10.1515/REVEH.2007.22.2.91
34. Lavoie RA, Bouffard A, Maranger R, Amyot M. Mercury transport
and human exposure from global marine fisheries. Sci Rep. (2018)
8:6705. doi: 10.1038/s41598-018-24938-3
35. Park JD, Zheng W. Human exposure and health effects of inorganic
and elemental mercury. J Prevent Med Public Health. (2012)
45:344. doi: 10.3961/jpmph.2012.45.6.344
36. Graves CA, Powell A, Stone M, Redfern F, Biko T, Devlin M. Marine water
quality of a densely populated Pacific atoll (Tarawa, Kiribati): cumulative
pressures and resulting impacts on ecosystem and human health. Mar Pollut
Bull. (2021) 163:111951. doi: 10.1016/j.marpolbul.2020.111951
37. Llewellyn LE. Revisiting the association between sea surface temperature
and the epidemiology of fish poisoning in the South Pacific: reassessing
the link between ciguatera and climate change. Toxicon. (2010) 56:691–
7. doi: 10.1016/j.toxicon.2009.08.011
38. Friedman MA, Fernandez M, Backer LC, Dickey RW, Bernstein J,
Schrank K, et al. An updated review of ciguatera fish poisoning: clinical,
epidemiological, environmental, and public health management. Mar Drugs.
(2017) 15:72. doi: 10.3390/md15030072
39. Soliño L, Costa PR. Global impact of ciguatoxins and ciguatera
fish poisoning on fish, fisheries and consumers. Environ Res. (2020)
182:109111. doi: 10.1016/j.envres.2020.109111
40. Chan WH, Mak YL, Wu JJ, Jin L, Sit WH, Lam JCW, et al. Spatial distribution
of ciguateric fish in the republic of Kiribati. Chemosphere. (2011) 84:117–
123. doi: 10.1016/j.chemosphere.2011.02.036
41. Kibler SR, Tester PA, Kunkel KE, Moore SK, Litaker RW. Effects of ocean
warming on growth and distribution of dinoflagellates associated with
ciguatera fish poisoning in the Caribbean. Ecol Model. (2015) 316:194–
210. doi: 10.1016/j.ecolmodel.2015.08.020
42. Skinner MP, Brewer TD, Johnstone R, Fleming LE, Lewis RJ. Ciguatera fish
poisoning in the Pacific Islands (1998 to 2008). PLoS Negl Trop Dis. (2011)
5:e1416. doi: 10.1371/journal.pntd.0001416
43. Smith KR, Ezzati M. How environmental health risks change
with development: the epidemiologic and environmental risk
transitions revisited. Annu Rev Environ Resour. (2005) 30:291–
333. doi: 10.1146/annurev.energy.30.050504.144424
44. Lewis ND, Rapaport M. In a sea of change: health transitions in the Pacific.
Health Place. (1995) 1:211–26. doi: 10.1016/1353-8292(95)00030-5
45. Chung MG, Li Y, Liu J. Global red and processed meat trade
and non-communicable diseases. BMJ Glob Health. (2021)
6:e006394. doi: 10.1136/bmjgh-2021-006394
46. Sievert K, Lawrence M, Naika A, Baker P. Processed foods and nutrition
transition in the pacific: regional trends, patterns and food system drivers.
Nutrients. (2019) 11:1328. doi: 10.3390/nu11061328
47. Popkin BM. The nutrition transition in low-income countries: an emerging
crisis. Nutr Rev. (2009) 52:285–98. doi: 10.1111/j.1753-4887.1994.tb01460.x
48. FAO. Fishery and Aquaculture Country Profiles: The Republic of Kiribati. FAO
(2021). Available online at: https://www.fao.org/fishery/facp/KIR/en
49. Gillett R. Fisheries in the Economies of Pacific Island Countries and Territories.
Pacific Community, Forum Fisheries Agency, Australian Aid (2016).
5. Golden CD, Gephart JA, Eurich JG, McCauley DJ, Sharp MK, Andrew NL,
et al. Social-ecological traps link food systems to nutritional outcomes. Glob
Food Secur. (2021) 30:100561. doi: 10.1016/j.gfs.2021.100561
6. Troubat N, Sharp MK. Food consumption in Kiribati – Based on analysis of
the 2019/20 Household Income and Expenditure Survey. Tarawa: FAO and
SPC (2021).
7. Thomas FR. Shellfish gathering in Kiribati, micronesia: nutritional,
microbiological, andtoxicological aspects. Ecol Food Nutr. (2003)
42:91–127. doi: 10.1080/03670240390202246
8. Golden CD, Seto KL, Dey MM, Chen OL, Gephart JA, Myers SS, et al. Does
aquaculture support the needs of nutritionally vulnerable nations?. Front Mar
Sci. (2017) 1:159. doi: 10.3389/fmars.2017.00159
9. Andrew NL, Allison EH, Brewer T, Connell J, Eriksson H, Eurich JG, et al.
Continuity and change in the contemporary Pacific food system. Glob Food
Secur. (2022) 32:100608. doi: 10.1016/j.gfs.2021.100608
10. Bell JD, Kronen M, Vunisea A, Nash WJ, Keeble G, Demmke A, et al.
Planning the use of fish for food security in the Pacific. Mar Policy. (2009)
33:64–76. doi: 10.1016/j.marpol.2008.04.002
11. Kiribati Ministry of Fisheries and Marine Resources Development. Kiribati
National Fisheries Policy 2013. Tarawa: Ministry of Fisheries and Marine
Resources Development, Government of Kiribati, Bairiki (2013).
12. Mangubhai S, Lovell E, Abeta R, Donner S, Redfern FM, O’Brien M,
et al. Kiribati: atolls and marine ecosystems. In: Sheppard C, editor.
World Seas: An Environmental Evaluation. London: Elsevier (2019) 807–26.
doi: 10.1016/B978-0-08-100853-9.00054-3
13. PopGIS3—Kiribati. Kiribati 2020 Census. PopGIS3—Kiribati. Retrieved from
https://kiribati.popgis.spc.int/#c=home (accessed March 4, 2022).
14. Campbell B, Hanich Q. Fish for the Future: Fisheries Development and
Food Security for Kiribati in an Era of Global Climate Change. Penang:
WorldFish (2014).
15. Kiribati Ministry of Fisheries and Marine Resources Development. A Draft
Strategic Framework for Institutional Strengthening in Fisheries Managements
and Development. Tarawa: MFMRD/FFA/ SPC; Kiribati Ministry of Fisheries
and Marine Resources Development (2011).
16. Donner S. Sea level rise and the ongoing battle of Tarawa. Eos Trans Am
Geophys Union. (2012) 93:169–70. doi: 10.1029/2012EO170001
17. Donner
SD.
Fantasy
island.
Sci
Am.
(2015)
312:56–
63. doi: 10.1038/scientificamerican0315-56
18. Donner SD, Webber S. Obstacles to climate change adaptation decisions:
a case study of sea-level rise and coastal protection measures in Kiribati.
Sustainability Science. (2014) 9:331–45. doi: 10.1007/s11625-014-0242-z
19. Lough JM, Meehl GA, Salinger MJ. Observed and Projected Changes in
Surface Climate of the Tropical Pacific. Noumea: Vulnerability of Tropical
Pacific Fisheries and Aquaculture to Climate Change; Secretariat of the Pacific
Community (2011).
20. Bell JD, Johnson JE, Hobday AJ. Vulnerability of Tropical Pacific Fisheries and
Aquaculture to Climate Change. Noumea: SPC FAME Digital Library (2011).
21. Australian Bureau of Meteorology and Commonwealth Scientific and
Industrial Research Organization. Climate Change in the Pacific: Scientific
Assessment and New Research. Vol. 2: Country reports. Canberra, ACT:
Australian Bureau of Meteorology and Commonwealth Scientific and
Industrial Research Organization (2011).
22. Cannon SE, Aram E, Beiateuea T, Kiareti A, Peter M, Donner SD.
Coral reefs in the gilbert islands of Kiribati: resistance, resilience, and
recovery after more than a decade of multiple stressors. PLoS ONE. (2021)
16:e0255304. doi: 10.1371/journal.pone.0255304
23. Donner SD, Carilli J. Resilience of central Pacific reefs subject
to frequent heat stress and human disturbance. Sci Rep. (2019)
9:3484. doi: 10.1038/s41598-019-40150-3
24. Richardson LE, Graham NA, Pratchett MS, Eurich JG, Hoey AS. Mass coral
bleaching causes biotic homogenization of reef fish assemblages. Glob Change
Biol. (2018) 24:3117–29. doi: 10.1111/gcb.14119
25. Campbell JR. Climate Change and Urbanization in Pacific Island Countries.
Policy Brief No. 49. Tokyo: Toda Peace Institute (2019).
26. Thow AM, Heywood P, Schultz J, Quested C, Jan S, Colagiuri S. Trade
and the nutrition transition: strengthening policy for health in the
pacific. Ecol Food Nutr. (2011) 50:18–42. doi: 10.1080/03670244.2010.52
4104
Frontiers in Public Health | www.frontiersin.org
19
June 2022 | Volume 10 | Article 890381
Golden et al.
Reef Fisheries and Human Nutrition
72. Statistics for Development Division, Pacific Nutrient DataBase 2020 (PNDB
2020), Version 01 of the public-use dataset (July 2020), provided by the
Pacific Data Hub - Microdata Library. Available online at: https://microdata.
pacificdata.org/index.php/home
73. World Health Organization. Haemoglobin Concentrations for the Diagnosis
of Anaemia and Assessment of Severity (No. WHO/NMH/NHD/MNM/11.1).
Geneva: World Health Organization (2011).
74. Carey RM, Whelton PK. Prevention, detection, evaluation, and management
of high blood pressure in adults: synopsis of the 2017 american college of
cardiology/American heart association hypertension guideline. Ann Intern
Med. (2018) 168:351–8. doi: 10.7326/M17-3203
75. Grundy SM, Cleeman JI, Daniels DKA, Eckel RH, Franklin BA,
Gordon DJ, et al. Diagnosis and management of the metabolic
syndrome—an American heart association/national heart, lung,
and blood institute scientific statement—Executive summary.
Circulation. (2005) 112:E285–90. doi: 10.1161/CIRCULATIONAHA.105.
169405
76. Warnick GR, Knopp RH, Fitzpatrick V, Branson L. Estimating low-density
lipoprotein cholesterol by the friedewald equation is adequate for classifying
patients on the basis of nationally recommended cutpoints. Clin Chem. (1990)
36:15–9. doi: 10.1093/clinchem/36.1.15
77. Tozzi V, Rosenberger A, Kube D, Bickeböller H. Global, pathway and
gene coverage of three illumina arrays with respect to inflammatory
and immune-related pathways. Euro J Hum Genet. (2019) 27:1716–
23. doi: 10.1038/s41431-019-0441-2
78. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D,
et al. PLINK: a tool set for whole-genome association and populationbased linkage analyses. Am J Hum Genet. (2007) 81:559–75. doi: 10.1086/
519795
79. Pagana K, Pagana T, Pagana T. Mosby’s Diagnostic & Laboratory Test Reference.
14th edition. St. Louis, MO: Elsevier (2019).
80. Heenan A, Ayotte P, Gray A, Lino K, Mccoy K, Zamzow J, et al. Ecological
Monitoring 2012–2013: Reef Fishes and Benthic Habitats of the Main Hawaiian
Islands, American Samoa, and Pacific Remote Island Areas. PIFSC Data Report
DR-14–R003. Washington, DC: National Oceanographic and Atmospheric
Administration (2014).
81. Parravicini V, Casey JM, Schiettekatte NM, Brandl SJ, PozasSchacre C, Carlot J, et al. Delineating reef fish trophic
guilds with global gut content data synthesis and phylogeny.
PLoS
Biol.
(2020)
18:e3000702.
doi:
10.1371/journal.pbio.30
00702
82. Mora C, Aburto-Oropeza O, Ayala Bocos A, Ayotte PM, Banks S,
Bauman AG, et al. Global human footprint on the linkage between
biodiversity and ecosystem functioning in reef fishes. PLoS Biol. (2011)
9:e1000606. doi: 10.1371/journal.pbio.1000606
83. Norström AV, Nyström M, Jouffray, J.-B., Folke C, Graham NA, et al. Guiding
coral reef futures in the anthropocene. Front Ecol Environ. (2016) 14:490–
8. doi: 10.1002/fee.1427
84. Darling ES, McClanahan TR, Maina J, Gurney GG, Graham NA, JanuchowskiHartley F, et al. Social–environmental drivers inform strategic management
of coral reefs in the anthropocene. Nat Ecol Evol. (2019) 3:1341–
50. doi: 10.1038/s41559-019-0953-8
85. Graham NAJ, Nash KL. The importance of structural complexity in
coral reef ecosystems. Coral Reefs. (2013) 32:315–26. doi: 10.1007/s00338012-0984-y
86. De’ath G, Fabricius K. Water quality as a regional driver of coral biodiversity
and macroalgae on the Great Barrier Reef. Ecol. Appl. (2010) 20:840–50.
doi: 10.1890/08-2023.1
87. Schaffelke B, Carleton J, Skuza M, Zagorskis I, Furnas MJ. (2012). Water
quality in the inshore Great Barrier Reef lagoon: Implications for longterm monitoring and management. Mar. Pollut. Bull. (2012) 65:249–60.
doi: 10.1016/j.marpolbul.2011.10.031
88. Paerl HW. Mitigating toxic planktonic cyanobacterial blooms in aquatic
ecosystems facing increasing anthropogenic and climatic pressures. Toxins.
(2018) 10:76. doi: 10.3390/toxins10020076
89. Specht AJ, Kponee K, Nkpaa KW, Balcom PH, Weuve J, Nie LH, et
al. Validation of x-ray fluorescence measurements of metals in toenail
clippings against inductively coupled plasma mass spectrometry in a Nigerian
50. Pacific Community. Household Income and Expenditure Survey: Kiribati,
2019–2020. Pacific Community (2021). Available online at: http://microdata.
pacificdata.org/index.php/catalog/760
51. Dehouck P, Cordeiro F, Snell J, de la Calle B. State of the art in the
determination of trace elements in seawater: a worldwide proficiency test.
Anal Bioanal Chem. (2016) 408:3223–32. doi: 10.1007/s00216-016-9390-6
52. de Onis M. The WHO child growth standards. Pediatr Nutr Pract. (2008)
113:254–69. doi: 10.1159/000155527
53. Harris WS, Del Gobbo L, Tintle NL. The omega-3 index and relative risk
for coronary heart disease mortality: estimation from 10 cohort studies.
Atherosclerosis. (2017) 262:51–4. doi: 10.1016/j.atherosclerosis.2017.05.007
54. Bellwood DR, Hemingson CR, Tebbett SB. Subconscious biases in coral reef
fish studies. BioScience. (2020) 70:621–7. doi: 10.1093/biosci/biaa062
55. Eurich JG, McCormick MI, Jones GP. Habitat selection and aggression
as determinants of fine-scale partitioning of coral reef zones in a
guild of territorial damselfishes. Mar Ecol Prog Ser. (2018) 587:201–
15. doi: 10.3354/meps12458
56. Hay ME. The functional morphology of turf-forming seaweeds: persistence in
stressful marine habitats. Ecology. (1981) 62:739–50. doi: 10.2307/1937742
57. Kelley R. Indo Pacific Coral Finder. 3rd ed. Townsville, QLD: Byoguides
(2016).
58. Marshall NJ, Kleine DA, Dean AJ. CoralWatch: education, monitoring, and
sustainability through citizen science. Front Ecol Environ. (2012) 10:332–
4. doi: 10.1890/110266
59. Siebeck UE, Marshall NJ, Klüter A, Hoegh-Guldberg O. Monitoring coral
bleaching using a colour reference card. Coral Reefs. (2006) 25:453–
60. doi: 10.1007/s00338-006-0123-8
60. Pakoa K, Friedman K, Moore B, Tardy E, Bertram I. Assessing Tropical
Marine Invertebrates: A Manual for Pacific Island Resource Managers. Nomea:
Secretariat of the Pacific Community (2014).
61. Eurich JG, Shomaker SM, McCormick MI, Jones GP. Experimental
evaluation of the effect of a territorial damselfish on foraging behaviour
of roving herbivores on coral reefs. J Exp Mar Biol Ecol. (2018) 506:155–
62. doi: 10.1016/j.jembe.2018.06.009
62. Willis TJ, Millar RB, Babcock RC. Detection of spatial variability in
relative density of fishes: comparison of visual census, angling, and baited
underwater video. Mar Ecol Prog Ser. (2000) 198:249–60. doi: 10.3354/meps1
98249
63. Cappo M, Harvey E, Shortis M. Counting and measuring fish with baited
video techniques - an overview. In: Lyle JM, Furlani DM, Buxton CD,
editors. Cutting-Edge Technologies in Fish and Fisheries Science. Hobart, TAS:
Australian Society for Fish Biology Workshop Proceedings (2006).
64. Arar EJ, Collins GB. Method 445.0: In vitro Determination of Chlorophyll a and
Pheophytin a in Marine and Freshwater Algae by Fluorescence. Washington,
DC: United States Environmental Protection Agency (1997).
65. Kennish MJ. Pollution Impacts on Marine Biotic Communities. Vol. 14. Boca
Raton, FL: CRC Press (2019). doi: 10.1201/9781003069003
66. de Souza AFL, Petenuci ME, Camparim R, Visentainer JV, da Silva AJI.
Effect of seasonal variations on fatty acid composition and nutritional profiles
of siluriformes fish species from the amazon basin. Food Res Int. (2020)
132:109051. doi: 10.1016/j.foodres.2020.109051
67. Allam H, Aouar A, Benguedda W, Bettioui R. Use of sediment and algae for
biomonitoring the coast of Honaïne (Far West Algerian). Open J Ecol. (2016)
6:159. doi: 10.4236/oje.2016.64016
68. Gopinath A, Muraleedharan NS, Chandramohanakumar N, Jayalakshmi
KV. Statistical significance of biomonitoring of marine algae for
trace metal levels in a coral environment. Environ For. (2011)
12:98–105. doi: 10.1080/15275922.2011.547440
69. Jiang Y, Chen Y, Alrashdi M, Luo W, Tang BZ, Zhang J, et al. Monitoring
and quantification of the complex bioaccumulation process of mercury ion
in algae by a novel aggregation-induced emission fluorogen. RSC Adv. (2016)
6:100318–100325. doi: 10.1039/C6RA22190D
70. Mantyka CS, Bellwood DR. Direct evaluation of macroalgal
removal by herbivorous coral reef fishes. Coral Reefs. (2007)
26:435–42. doi: 10.1007/s00338-007-0214-1
71. Connell SD, Foster MS, Airoldi L. What are algal turfs? Towards
a better description of turfs. Mar Ecol Prog Ser. (2014) 495:299–
307. doi: 10.3354/meps10513
Frontiers in Public Health | www.frontiersin.org
20
June 2022 | Volume 10 | Article 890381
Golden et al.
Reef Fisheries and Human Nutrition
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and do not necessarily represent those of their affiliated organizations, or those of
the publisher, the editors and the reviewers. Any product that may be evaluated in
this article, or claim that may be made by its manufacturer, is not guaranteed or
endorsed by the publisher.
population. Physiol Measure. (2018) 39:085007. doi: 10.1088/1361-6579/aa
d947
90. Hardison DR, Holland WC, McCall JR, Bourdelais AJ, Baden DG, Darius HT,
et al. Fluorescent receptor binding assay for detecting ciguatoxins in fish. PLoS
ONE. (2016) 11:e0153348. doi: 10.1371/journal.pone.0153348
91. Swinburn BA, Kraak VI, Allender S, Atkins VJ, Baker PI, Bogard
JR, et al. The global syndemic of obesity, undernutrition, and
climate change: the lancet commission report. Lancet. (2019)
393:791–846. doi: 10.1016/S0140-6736(18)32822-8
Copyright © 2022 Golden, Ayroles, Eurich, Gephart, Seto, Sharp, Balcom,
Barravecchia, Bell, Gorospe, Kim, Koh, Zamborain-Mason, McCauley, Murdoch,
Nair, Neeti, Passarelli, Specht, Sunderland, Tekaieti, Tekiau, Tekoaua and
Timeon. This is an open-access article distributed under the terms of the
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terms.
Conflict of Interest: WK finished his contribution to this article prior to leaving
the Harvard T.H. Chan School of Public Health for a position at Impossible Foods.
JK was employed by the BAO Systems.
The remaining authors declare that the research was conducted in the absence of
any commercial or financial relationships that could be construed as a potential
conflict of interest.
Frontiers in Public Health | www.frontiersin.org
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June 2022 | Volume 10 | Article 890381