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1
The perception of odor pleasantness is shared across
cultures
Artin Arshamian1, Richard C. Gerkin2, Nicole Kruspe3, Ewelina Wnuk4, Simeon Floyd5,
Carolyn O'Meara6, Gabriela Garrido Rodriguez7, Johan N. Lundström1,8,9,
Joel D. Mainland8,10, & Asifa Majid11*
1 Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
2 School of Life Sciences, Arizona State University, Tempe, USA
3 Lund University, Sweden
4 University College London, UK
5 Universidad San Francisco de Quito, Ecuador
6 National Autonomous University of Mexico, Mexico
7University of Melbourne, Australia
8 Monell Chemical Senses Center, Philadelphia, USA
9 Stockholm University Brain Imaging Centre, Stockholm University, Stockholm, Sweden
10 University of Pennsylvania, Philadelphia, USA
11 University of York, UK
*Correspondence to Asifa Majid
Email: asifa.majid@york.ac.uk
Author Contributions: A.A., J.N.L., J.D.M., and A.M. designed research; N.K., E.W.,
S.F., C.O., and G.G.R. performed research; A.A. and R.C.G. analyzed data; and A.A.,
R.C.G., J.D.M. and A.M. wrote the paper.
Competing Interest Statement: No competing interests.
Classification: Biological Sciences; Psychological and Cognitive Sciences
Keywords: human olfaction, odor pleasantness, cross-cultural
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Abstract
Human sensory experience varies across the globe. Nonetheless, all humans share
sensory systems with a common anatomical blueprint. In olfaction, it is unknown to what
degree sensory perception, in particular the perception of odor pleasantness, is dictated
by universal biological principles versus sculpted by culture. To address this issue, we
asked 235 individuals from 9 diverse non-western cultures to rank the hedonic value of
monomolecular odorants. We observed substantial global consistency, with molecular
identity explaining 41% of the variance in individual pleasantness rankings, while culture
explained only 6%. These rankings were predicted by the physicochemical properties of
out-of-sample molecules and out-of-sample pleasantness ratings given by a separate
group of industrialized western urbanites, indicating human olfactory perception is
strongly constrained by universal principles.
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Introduction
In 1878 Margaret Wolfe Hungerford wrote that “Beauty is in the eye of the beholder”,
suggesting that what one person finds beautiful, another may not. Similar to beauty,
some argue that odor preference or valence is subjective—varying from person to
person as well as across cultures (1–7). Fermented herring, for example, emits a smell
described as the “most repulsive in the world,” but is a greatly appreciated delicacy in
Sweden (8). At the same time, odor valence is considered to be the principal perceptual
dimension by which odors are categorized and can be objectively predicted from
chemical structure (9–11). It is unclear how to reconcile these perspectives: is odor
preference entirely culturally relative or is it universally constrained by molecular
structure? To address this, we designed a study to disentangle the influence of individual
variability, cultural influence, and physicochemical properties on the perception of odor
valence.
Previous studies attempting to address this question have been limited in a number of
ways. Some studies take an ethnographic approach with traditional communities. These
provide valuable insight into lesser-described cultures very different to western
urbanites, but typically the studies are observational and focus on single odors that
illustrate radical cross-cultural differences in odor preferences (2, 6). Other studies using
an experimental approach have found universals in odor preferences; but these studies
default to testing people with similar lifestyles and experiences—i.e., literate, educated,
and technologically savvy individuals who partake of a common global fragrance and
flavor industry (12, 13). In this study, a network of fieldworkers collected new
experimental data regarding perceived odor pleasantness from nine diverse non-western
communities sampled across varying subsistence styles, ecologies, and geographies.
Critically, seven of these groups belonged to small-scale societies—including hunter-
gatherers, horticulturalists, and subsistence agriculturalists—with a more traditional
lifestyle and who do not experience the same chemical ecology as western urbanites
(Fig. 1 and Methods).
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Figure 1. Cross-cultural sample. Odor preference ratings were taken from ten culturally and
geographically diverse populations. These included the three hunter-gatherer groups, Seri,
Maniq, and Semaq Beri, from a coastal desert and tropical rainforest respectively; one shoreline
forager, Mah Meri, from a tropical coast; one swidden-horticulturalist, Semelai, from tropical
rainforest; one farmer-foraging community, Chachi, from tropical rainforest; one subsistence
agriculturalist, Imbabura Quichua, from temperate highlands; and three urban dwellers from
industrial and post-industrial communities of bustling urban settings, Mexican, Thai, and
American New Yorkers.
Results
Odorants were selected based on a previous study with post-industrial urban dwellers
from New York City (USA) who rated the pleasantness of 476 diverse molecules (14). We
selected ten of these odorants such that the mean ratings would span the valence
dimension from unpleasant to pleasant (for more details see Methods). Participants from
the nine new communities were presented with ten pen-like odor-dispensing devices (15),
each containing a unique odorant. A rank-order paradigm was chosen to assess odor
pleasantness because not all groups had numeracy, and use of scales and ratings is not
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the norm in these communities. The pens were randomly ordered and placed in a line that
faced the subject. The participant first smelled all the odors in front of them and then
ordered the pens from most pleasant to most unpleasant (from their left-to-right).
If odor valence is universal, then all groups should rank odors in the same way. If, on the
other hand, odor valence is learned from exposure to cultural traditions, then societies
should differ in their perceived odor pleasantness, with a diverse set of rank orders across
cultures. Using the within-culture mean ranking for each odorant, we found that odor
valence rankings correlated strongly and positively across all cultures (Fig. 2, r = 0.82 ±
0.18), supporting the idea that culture has a relatively small influence overall on odor
pleasantness.
Figure 2. Pleasantness rankings across individuals and cultures. Between n=16 and n=55
individuals from each culture ranked each of 10 odorants in order from most (1, blue) to least (10,
red) pleasant. Each color patch represents the integer ranking that one individual (from the
culture indicated at the top) gave to one odorant (indicated on the left). The broad column on the
far right represents the average ranking for each odorant across all individuals. Pleasantness
rankings were also correlated for both the most pleasant and most unpleasant odorants
(Supplementary Results Fig. S1).
We estimated the influence of culture, individual variability, and universal structure on odor
valence using both frequentist and Bayesian statistical inference. The frequentist
approach showed that a universal structure explained 41% of the variance in rankings,
while culture explained only 6% (Fig. 3). The remaining 54% of the variance was due to
individual variability, driven by some combination of individual preferences and perceptual
noise. As a positive control, we simulated a case where culture drives odor preference by
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shuffling odor labels in a manner that was consistent for each member of a culture but
varied across cultures. Under these conditions, 41% of the variance was explained by
culture (Supplementary Results Fig. S2). This positive control shows that our method is
sensitive enough to measure cultural variability should it exist. As a negative control for a
possible effect of culture, we then shuffled individuals between cultures. Under these
conditions, culture only explained 2% of the variance (Supplementary Results Fig. S2),
not much smaller than the value observed in the unshuffled data. The analogous Bayesian
model comparisons reached the same conclusions (Supplementary Results Fig. S3-S4).
Consistent with only a small contribution for culture, direct assessment of inter-individual
ranking similarity using Kendall’s tau showed that mean rank similarity for pairs of
individuals within the same culture (tau = 0.32 ± 0.14) was only slightly higher than for
pairs of individuals in different cultures (0.28 ± 0.11). In addition, a follow-up intensity
ranking task showed that pleasantness ranking was not explained by the perceived
intensity of the odorants (SI Appendix 1 and Supplementary Results Fig. S5). In summary,
across the ten cultures we found only a weak contribution of culture to odor valence
rankings.
Figure 3. Effect size
𝜼𝟐
from a two-way ANOVA for each of three factors that could
potentially explain each individual’s pleasantness rankings. Culture membership (purple,
6%) plays a negligible role in explaining the variance in the observed odor pleasantness rankings;
whereas Odorant identity (green, 41%) and Individual variability (orange, 54%) explain more.
If odor valence is mostly universal, then it should be possible to predict odor valence
directly. Specifically, if physicochemical properties of odorants are the primary determinant
of odor valence, the mean rank order from each culture should be predictable by a model
trained using valence assessments made by a single culture. To do this we used the
remaining 466 odorants from the original New York City data—excluding our 10 test
odorants—to build a predictive model using the best random-forest algorithm from the
DREAM Olfaction challenge applied to computed physicochemical features of each
molecule (16). We then computed the rank order similarity between all pairs of individuals
(including the model) using Kendall’s tau. For each and every culture, the within-culture
mean rank order was more highly correlated with predictions from the model (on the test
10 odorants) than with any random participant from the same culture (Fig. 4). In other
words, a universal model trained on responses of western urbanites to an independent
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set of odorants was at least as good a predictor of the culturally and ecologically diverse
field data we collected here than data from the same culture and same set of odors.
Figure 4. A universal model for odor pleasantness explains individual odor preferences.
(A) The correlation of odor pleasantness rankings (Kendall’s
𝜏
) between each individual and other
individuals from their culture (x-axis) is similar to the correlation between each individual and the
entire population studied here. The hunter-gatherer Maniq showed the lowest correlation to other
groups and to each other, with no cultural consensus. Critically, the Maniq do not demonstrate a
systematic alternative cultural odor preference; merely high levels of individual variation. A control
task showed this was not because they misunderstood the ranking task (Supplementary Results
Fig. S6). Differences in individual agreement across cultures could be explained by differences in
the reliability of the instrument at different locations. (B) Rankings predicted by a computational
model trained on perceived pleasantness ratings for out-of-sample odorants are more correlated
with individual rankings for the odorants used here than are other individuals from the same
culture.
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Discussion
Taken together, our results demonstrate that odor valence perception is largely
independent of cultural factors such as subsistence style and ecology, and can be
predicted from physicochemical properties. This is striking, and contrary to what would
have been predicted from a cultural relativity perspective (1–7, 17, 18). While it is widely
accepted that valence is the principal perceptual axis of olfaction (9–12, 19), there has
also been wide support for the idea that most aspects of olfactory perception are highly
malleable and mainly learned (1–7, 17, 18, 20, 21), and importantly have little to do with
an odorant’s physicochemical properties (22). Odor pleasantness is demonstrably plastic
and modulated by factors such as early exposure (23, 24) and context (25–30). Our data
do not adjudicate between learned versus innate explanations of odor pleasantness
perception. Global regularities in odor perception could indicate common and shared
experiences across all human groups. Infant data from diverse cultural contexts could
adjudicate between these possibilities; although even here there are challenges since
the fetus is already being enculturated into a specific chemical environment (31).
Nevertheless, our data demonstrate that physicochemical structure, rather than culture,
seems to be the primary predictor of the pleasantness of most odors. This is also
reflected in the fact that odor valence is shared across a wide range of species, possibly
due to processes at the receptor level that may shape the valence for monomolecular
odorants as well as complex mixtures (32–36). Critically, we show there is a universal
bedrock of olfactory perception that is shared among all people.
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Materials and Methods
Sample.
Our sample consisted of data from 10 communities with diverse modes of subsistence
living in varied environments (Fig. 1). The data were collected and treated according to
the ethical guidelines of the American Psychological Association, and the protocol was
approved by the Ethics Assessment Committee at Radboud University. Informed
consent was obtained in writing or orally as appropriate to each community. We briefly
describe each community in turn.
Semaq Beri. The hunter-gatherer Semaq Beri live in the northeast of the Malay
Peninsula. Traditionally they moved about the tropical rainforests in small bands of eight
to ten families, making temporary camps of lean-to shelters, hunting and fishing, and
foraging for the many kinds of wild tubers and seasonal fruits. They have become
increasingly sedentized since the establishment of resettlement villages in the mid-
1970s. The participants in this study live in a village of around 300 people, and maintain
a forest-based subsistence mode. They speak the Semaq Beri language which belongs
to the Austroasiatic language family. The total Semaq Beri population is approximately
2,300. Sample: There were 25 subjects (13 female and 12 male, Mage = 33.3 years, SD =
14.3 years) a number that is equivalent to approximately 1% of the total Semaq Beri
population.
Maniq. The Maniq inhabit a mountainous region in the interior of isthmian Thailand. The
area is covered by tropical evergreen forest. Maniq subsistence is hunting, gathering,
and exchange of forest products for food. The Maniq population is around 300 with the
size of a residential group varying day-to-day, usually close to 25-35. The group lives in
temporary camps in the rainforest with minimal material possessions. Maniq is the main
and first language, although everyone can understand and speak Southern Thai (with
varying degrees of proficiency). Only a handful (<5) of Maniq have received basic
schooling and most are illiterate. Sample: There were 16 subjects (8 female and 8 male,
Mage = 33.4 years, SD = 12.5 years) a number that is equivalent to approximately 5% of
the total Maniq population.
Seri. The Seri are a traditionally hunter-gatherer-fisher, semi-nomadic people, but since
the mid-20th century they are now more sedentary. They take part in small-scale fishing
operations, small ecotourism enterprises, sell permits to hunt on their land, work as
hunting guides and benefit from the sale of arts and crafts, especially baskets made of
desert limberbush. Seri live in 2 small villages in northwestern Mexico, along the coast of
the Gulf of California in the Sonoran Desert. Their traditional homeland includes the
biggest island in Mexico, Tiburon Island. The population size is between 900 and 1,000.
The Seri people speak the Seri language. The participants in this study were from the
village El Desemboque de los Seris, Sonora. Sample: There were 25 subjects (19
female and 6 male, Mage = 39.3 years, SD = 16.4 years) a number that is equivalent to
approximately 2.5% of the total Seri population.
Semelai. The Semelai reside in the southwest of the Malay Peninsula in an area of
lowland tropical rainforest. Traditionally they dwelt in small family groups scattered
throughout the forest, growing rice in swiddens, fishing and hunting, and collecting forest
products like rattan and resin for trade. Today the Semelai live primarily in resettlement
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villages of a few hundred people, and most are small-holder rubber tappers. They
continue to fish and hunt. The Semelai speak the Austroasiatic language Semelai. Their
total population is around 5,000. Sample: There were 25 subjects (13 female and 12
male, Mage = 38.3 years, SD = 13.8 years) a number that is equivalent to approximately
0.5% of the total population.
Mah Meri. The Mah Meri reside on the southwest coast of the Malay Peninsula in a rural
landscape that has been dominated by rubber and palm oil plantations since the early
1900s. Traditionally the Mah Meri engaged in shoreline foraging along the mangrove-
lined coast, hunting in the forest, and growing rice and other subsistence crops around
their homesteads. Resettlement villages of several hundred people were founded in the
mid-20th century. Cash-cropping was introduced, first coffee then palm oil, but the
scarcity of land has long caused people to seek external employment, while others fish,
or forage the shoreline. They speak Mah Meri, an Austroasiatic language. There are
around 3,500 Mah Meri people. Sample: There were 25 subjects (13 female and 12
male, Mage = 39.4 years, SD = 15.7 years) a number that is equivalent to approximately
0.7% of the total Mah Meri population.
Imbabura Quichua. Imbabura Quichua people live in agricultural communities, planting
crops like corn and potatoes, but are also famous for their long historical tradition of
weaving which has developed into an important handcraft industry. Like the other
Highland Quichua people of Ecuador, they speak a local variety of the Ecuadorian
Highland Quichua language descended from the Quechua language introduced by the
Incas from modern Peru. While many Imbabura Quichua people maintain a traditional
rural lifestyle, eat local food, and speak mainly Quichua, others are connected to the
national and overseas economies through trade, travel, and the tourism industry, and
are bilingual in Spanish; both types of participants were included in the study, conducted
in a semi-rural, semi-urban area. Sample: There were 25 subjects (14 female and 11
male, Mage = 43 years, SD = 15.7 years) a number that is equivalent to approximately
0.0004% of the total Imbabura Quichua population of approximately 60,000.
Chachi. Traditionally the Chachi lived in isolated homesteads but today they live in small
communities along the Cayapas river and its tributaries. Their lifestyle is mainly based
on subsistence agriculture, with plantain as the basic staple, in addition to fishing and
hunting. They also plant cash crops like cacao and engage in other activities like
basketwork and logging, and use income to purchase outside supplies such as white
rice, which has become an important staple in recent years. Their language is called
Cha’palaa, from the Barbacoan language family. Participants are from a remote rural
area where local people maintain a relatively traditional and autonomous lifestyle in
which Cha’palaa is the dominant language and Spanish is used by a minority who have
some experience outside the community. Sample: There were 25 subjects (13 female
and 12 male, Mage = 44.6 years, SD = 14.9 years) a number that is equivalent to
approximately 0.0025% of the total Chachi population of about 10,000.
Mexican. Mexico is a country with a population of 126 million. Mexico is considered to be
ethnically diverse. Group residence varies considerably with large cities having many
millions whereas small towns can have populations in the thousands or less. Our sample
of subjects came from Mexico City which has a population of approximately 8.9 million
people. The majority of the participants of the study were university employees (e.g.,
office workers). All subjects had access to all modern technologies (e.g., internet and
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television). The subjects were tested in Mexican Spanish. Sample: There were 35
subjects (19 female and 13 male, Mage =39.8 years, SD = 15.5 years) a number that is
equivalent to approximately 0.000004% of the total Mexico City population.
Thai. Thailand has a population of almost 70 million with a mixture of ethnic groups. The
data for this study was collected on the campus of the University of Ubon Ratchathani in
Northeastern Thailand. The city of Ubon Ratchathani is a capital and an urban center of
the province Ubon Ratchathani with 1.87 million inhabitants. Sample: The participants
were from Ubon University and included university students and university employees
(instructors, guards, cooks, shopkeepers). All subjects had access to all modern
technologies (e.g., internet, television, etc.). The subjects were tested in Thai. There
were 27 subjects (16 female and 11 males, Mage = 30 years, SD = 14.2 years) a number
that is equivalent to approximately 0.000014% of the total of Ubon Ratchathani province.
New Yorkers. USA is a country with a population of 328 million. Group residence varies
considerably with large cities having many millions whereas small towns can have
populations in the thousands. Our sample of subjects came from New York City, a
racially and ethnically diverse city, which has a population of approximately 8.4 million
people. Sample: There were 55 subjects (33 female and 22 male, Mage = 34.6 years, SD
= 9.5 years) a number that is equivalent to approximately 0.0000065% of the total New
York City population.
Materials.
Stimuli were presented in Sniffin’ Sticks (Burghardt®, Wedel, Germany) permeated with
the odor diluted in mineral oil. The ten odors, all from Sigma-Aldrich, used the DREAM
Olfaction Prediction Challenge dilution series (1): Isovaleric acid (CAS 503-74-2;
1/100,000 volume/volume), Diethyl disulfide (CAS 110-81-6; 1/1000), Octanoic acid
(CAS 124-07-2; 1/1000), 2-Isobutyl-3-methoxypyrazine (CAS 24683-00-9; 1/1000), 1-
Octen-3-ol (CAS 3391-86-4; 1/1000), 2-Phenylethanol (CAS 60-12-8; 1/1000), Ethyl
butyrate (CAS 105-54-4; 1/1000), Eugenol (CAS 97-53-0; 1/1000), Linalool (CAS 78-70-
6; 1/1000), and Vanillin (CAS 121-33-5; 1/10).
Procedure.
Our main experimental protocol was a pleasantness rank order task. As a control, we
also conducted an intensity rank order task. For the Maniq alone we conducted a
protocol validation task using pictorial stimuli.
Pleasantness rank order task. The odors were randomly ordered on a holder so they
made a line facing the subject. The subjects were told in their native language (i.e.,
Spanish, Seri, Imbabura Quichua, Cha’palaa, Thai, Maniq, Semelai, Semaq Beri, Mah
Meri) to initially smell all the odors in front of them (briefly and one at a time), and after
smelling all odors to order them from the most pleasant to the most unpleasant (their
left-to right). The experimenter made sure that subjects did not smell an odor more than
2-3 seconds and that there was an interstimulus interval of 20 seconds between odor
presentations. After subjects had smelled all odors on first encounter, they could freely
re-sample the odors again while ranking them. To verify that subjects had understood
the task correctly the experimenter asked them to point to the most pleasant and
unpleasant odor after they finished the rank order task.
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Intensity rank order task. Data collection was in two waves. In the first wave, data was
collected from the Maniq, Seri, Mexican and Thai. We suspected some odors were
vulnerable to the humid weather conditions in the Maniq site, one of the first to be tested,
although we were not able to measure this objectively at the time. In a second wave of
data collection, we collected data for judgements of odor intensity. The same
participants from five of the nine groups (Chachi, Imbabura Quichua, Semelai, Semaq
Beri, Mah Meri) that participated in the odor pleasantness rank order task also ranked
odors by intensity using the same paradigm. The subjects were told in their native
language that the task was first to smell all the odors in front of them (briefly and one at
a time) and then to order them from the strongest to the weakest (their left-to right). As
before, the experimenter made sure subjects did not smell the odor more than 2-3
seconds and that there was an interstimulus interval of 20 seconds between odor
presentations. Before the start of the intensity rank ordering of the odors, the subjects
undertook a control task to ensure they understood that they had to order odorants
according to intensity and not odor pleasantness. In this control task, four different
concentrations of the same odorant (i.e., 1-octen-3-ol in paraffin oil) were presented to
the subject in steps of: 1/10,000,000 (basically blank); 1/100; 1/10; and 100% 1-octen-3-
ol. To minimize adaptation effects, subjects first compared the two weakest
concentrations, then the two strongest concentrations, then the second strongest and
second weakest. Finally, they ordered odors from the strongest to the weakest (their left-
to-right).
Ranking protocol validation for Maniq. As the Maniq are not accustomed to formal
testing, we included a control to confirm that they could rank stimuli. We asked the same
Maniq participants to rank order a set of 8 photographs of animals according to their
hedonic value from most pleasant to most unpleasant (their left-to-right). We chose
animals that varied in hedonic values based on long-term ethnographic fieldwork with
the Maniq (Supplementary Results Fig. S6).
Statistical Analysis.
Full analysis details are provided in the Supplementary Analysis file. Code and data
have been provided to the reviewers and will be made publicly available upon
acceptance on GitHub at http://github.com/rgerkin/shared-pleasantness. Values reported
in the main text are mean ± standard deviation. Correlations are reported using
Pearson’s correlation (for means across groups) or Kendall’s tau (for comparisons
between individuals).
Acknowledgments
The fieldwork for this paper was funded by The Netherlands Organization for Scientific
Research, NWO VICI grant “Human olfaction at the intersection of language, culture and
biology” (Project number 277-70-011). This work was funded in part by the National
Institutes of Health (U19NS112953, R01DC018455). A.A was funded by a grant from the
Swedish Research Council (VR 2018-01603).
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