pica in pregnancy

 

Find and read a scholarly article  Were you familiar with Pica before? How did you know about it? What are some nursing interventions (at least four) that would apply to a pregnant woman who is being affected by this condition? Provide a summary of your scholarly article, and be sure to explain at least one overall conclusion about Pica from the study, that you think is important to state from the author’s research.

Introduction
Pica is an eating disorder in which a person intentionally
and frequently eats non-food items (1). Pica usually exists
in three forms: geophagy (eating soil and all soil-derived
materials such as white clay-red clay-brick-pottery),
amylophagy (eating rice and raw starch), and pagophagy
(eating ice and frozen materials) (2,3).

Due to the presence of bacteria, parasites, and heavy
metals in non-nutrient(1), Pica causes consequences
such as intestinal obstruction, interference with the
absorption of nutrients from the intestine, and electrolyte
disturbances (4). Some cultures, however, use these items
to treat gastrointestinal problems (5).

Pica is found in all races or cultures (1). but is more
common in poor areas, among children, lactating women,
and pregnant women (6).

In pregnancy, the mother’s need for nutrients increases
due to metabolic changes (7). Although adequate intake
of these substances is necessary to maintain the health of
mother and child (8,9), pica harms the mother and child by
substituting non-food items instead of food and preventing
the absorption of nutrients from the intestine (10). These
injuries include dental injuries, internal obstruction,
constipation, lead poisoning, parasitic infections, anemia,
hyperkalemia, malnutrition (10-12), preterm labor, low

birth weight, and increased mortality (11,13).
The prevalence of pica in pregnancy is between 0.7-67%.

For example: 74% in Kenya (14), 27% in India (15), 23% in
Argentine, 46% in America (16), and 60.5% in Iran (17).

Cultural traditions (increased breast milk), biological
factors (anemia, nutrient deficiency, cravings, reduced
nausea, and vomiting), demographic status, and midwifery
factors influence Pica practice (6,18).

Demographic factors such as celibacy (16), living in the
rural (10,17), low level of education (19-21), young age
(22), and unemployment (17) can increase the prevalence
of pica in women.

However, some studies have shown conflicting results
in terms of pica prevalence based on education level
(23), age (24), and employment (10,25). There is also no
relationship between maternal weight, body mass index
(BMI) before pregnancy, and gestational weight gain with
pica (16). In Santos and colleagues’ study, no correlation
was observed between weight and pica (13). In López
and colleagues’ study, BMI before pregnancy was not
associated with pica (23).

For obstetric factors, the prevalence of pica is higher in
the first trimester of pregnancy (26) and in nulliparous
women (8). However, some studies have shown different
findings (21,22).

Abstract
Objectives: Pregnancy pica is harmful to the mother and her baby. This study aimed to update the global prevalence of pica in
pregnant women.
Methods: Scopus, Science Direct, Wiley online, Google Scholar, and PubMed databases were searched for observational studies until
July 2021. This search was done with the keywords “pregnancy pica”, “prevalence of pica”, “pica frequency”. After evaluating the
extracted studies based on inclusion and exclusion criteria, 45 final articles were selected. Calculations were performed based on
STATA software. Publication bias was also assessed.
Results: The global prevalence of pica in pregnancy in the final forty-five articles (Sample size: 21 267) was 34%. However, the
prevalence has decreased since 2015. In the subgroup analysis, rural women, women with lower education, younger women,
unemployed women, and women living in the African geographical area had the highest prevalence of pica. Our results also showed
that this rate was higher in women in the first trimester of pregnancy and multiparous women.
Conclusions: The global prevalence of pica was 34%. Therefore, it is recommended to implement educational programs, empower
women and distribute nutritional supplements during pregnancy.
Keywords: Prevalence, Pica, Pregnant Woman, Meta-analysis

Update on the Global Prevalence of Pica in Pregnant
Women: A Meta-analysis
Shahrzad Sanjari1 ID , Mohammad Reza Mohammidi Soleimani2 ID , Azita Amir Fakhraei3* ID

Open Access Meta-analysis

International Journal of Women’s Health and Reproduction Sciences
Vol. 11, No. 3, July 2023, 99–110

http://www.ijwhr.net doi 10.15296/ijwhr.2023.18

ISSN 2330- 4456

Received 14 February 2022, Accepted 15 October 2022, Available online 11 March 2023

1Student Research Committee, School of Nursing and Midwifery, Shahroud University of Medical Sciences, Shahroud, Iran. 2Department of
Psychology, Kerman Branch, Islamic Azad University, Kerman, Iran. 3Psychology, Islamic Azad University of Bandar Abbas, Bandar Abbas, Iran.
*Corresponding Author: Azita Amir Fakhraei, Tel: +98-2332395054, Email: H09900318771@gmail.com

https://orcid.org/0000-0002-8773-5637

https://orcid.org/0000-0002-1496-2126

https://orcid.org/0000-0002-3753-0924

http://www.ijwhr.net

https://doi.org/10.15296/ijwhr.2023.18

http://crossmark.crossref.org/dialog/?doi=10.15296/ijwhr.2023.18&domain=pdf

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According to the millennium development goal to
eradicate poverty and malnutrition (27), the study of pica
in pregnancy can be a way to achieve this goal. Due to the
gap in studies on the prevalence of pica, a meta-analysis
is necessary.

In Fawcett’s meta-analysis, the global prevalence of pica
in pregnancy was 27.8% (28). According to numerous
studies conducted in recent years, performing a meta-
analysis helps to resolve inconsistencies and improve
therapeutic interventions. Therefore, this meta-analysis
was performed to determine the global prevalence of pica.

Methods
This meta-analysis was performed based on the PRISMA
checklist (29) by reviewing English language articles and
dissertations on the world until July 2021. The required
data were searched in Scopus, Science Direct, Google
Scholar, Wiley online, and PubMed databases using the
keywords “pregnancy pica”, “prevalence of pica”, and “pica
frequency”.

Selection of Studies
Inclusion criteria include observational studies in English
that report the prevalence of pica during pregnancy, high-
quality studies based on the Joanna Briggs Institute (JBI)
checklist. Exclusion criteria include non-observational
studies, articles without full text, and articles without data
to calculate the prevalence.

After searching for studies, duplicate, irrelevant, and
low-quality articles were removed. Finally, the information
needed to calculate the prevalence was extracted from
quality articles.

Quality Assessment
Studies that met the inclusion criteria of this meta-
analysis were evaluated using the JBI checklist (30). The
JBI checklist in cross-sectional studies comprises nine
questions with four answers: yes, no, uncertain and
unenforceable. We gave 1 point for each positive response.
Only studies with a minimum score of 5 entered the final
analysis. Search, extraction, and evaluation of the quality
of studies were performed by two researchers separately.
In case of disagreement, the view of the other researcher
was acceptable.

Statistical Analysis
Prevalence was assessed using meta-analysis in STATA
software (version 21). Cochrane Q test and I2 index were
used to evaluate the homogeneity between studies. After
confirming the heterogeneity of the studies (I2 index >
75%), the prevalence of pica was calculated by the effect
random model (31). The publication bias of the studies
was determined by the Begg test and sensitivity analysis
(30).

The review also assessed the prevalence of pica based
on the following subgroups: 1- Pica type (pagophagy,
geophagy, and amylophagy), 2- Year of publication (until
2015, after 2015), 3- Marital status (married, single), 4-
Residence (urban, rural), 5- Level of education (primary
or lower, upper primary), 6- Age (under 30, over 30
years), 7- Employment status (employed, unemployed),
8- Geographical region (Africa, America, and Asia), 9-
Pregnancy trimester (first, second and third trimesters)
and 10- Parity (nulliparous women, multiparous women).
The significance level of the Begg test was less than 0.05
(30).

Results
Initially, we found 452 articles. Finally, after deleting
406 studies (based on Figure 1), we included 45 final
articles with a sample size of 21267 in the meta-analysis.
Pica prevalence varied from 1.6% (32) to 76% (33)
among selected studies. A checklist containing articles
information is brought in Table 1.

Publication Bias
The Begg test value (P = 0.68) shows there is no publication
bias.

Meta-analysis
The prevalence of pica in pregnancy was 34% (95%
CI: 28%-41%) and the I2 index was 99.4% (P = 0.001)
(Figure 2).

Sensitivity Analysis
Excluding studies with a prevalence of less than 0.06
and above 0.7, no significant change was observed. The
range of change was between 32% (95% CI: 30–38%),
with Rainville (33) and Ngozi (14) excluded (Table 2), and
36% (95% CI: 31–43%), with Posner et al (32), Garg and
Sharma (52) and Jonathan et al (55) excluded (Table 3).

Subgroup Analysis – Pica Type
In this analysis, the overall prevalence of pagophagy,
geophagy, and amylophagy was assessed. The values
were 38% (heterogeneity: I2 = 99.5%, P = 0.001),
36% (heterogeneity: I2 = 98.7%, P = 0.001) and 27%
(heterogeneity: I2 = 99.9%, P = 0.001), respectively. Finally,
32% of women in our study had polypica (Figure 3).

Subgroup Analysis – Year of Study
In this analysis, 21 studies were related to before 2015, and

► Pica is the intentional eating of non-nutrients. This disorder
is common in children, lactating women, and pregnant
women.

► There have been many studies on the prevalence of pica
worldwide. Therefore, performing a meta-analysis helps to
understand the general situation.

► The prevalence of pica in pregnancy is affected by location,
level of education, age, employment, geographical area,
trimester of pregnancy, and parity.

Key Messages

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Figure 1. The Flowchart of the Study.

Figure 2. The Global Prevalence of Pica in Pregnancy.

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Table 1. Checklist of Articles Related to Pica Prevalence in Pregnancy

Author (year) Country
Study Design

Sample Size Prevalence Score of
Quality References

Cross-sectional Cohort

Lumish (2014) United States * 158 46% 6 (16)

Khoushabi (2014) Iran * 200 17.5% 6 (26)

Rainville (1998) United States * 281 76.5% 5 (33)

Mortazavi (2010) Iran * 560 15.5% 8 (24)

Konlan (2020) Ghana * 286 47.5% 6 (10)

Nana Adj (2016) Ghana * 265 10% 6 (34)

Young (2010) Tanzania * 2368 37.9% 8 (3)

Miller (2019) Africa * 371 45% 6 (1)

Mensah (2010) Africa * 400 47% 9 (35)

Roy (2017) United States * 187 37.6% 5 (20)

Santos (2017) Brazil * 913 5.7% 6 (13)

Ahmed (2012) Sudan * 396 40.5% 5 (36)

Geissler (1998) Africa * 275 56% 5 (37)

Patil (2012) Tanzania * 457 34% 6 (38)

Luoba (2004) Kenya * 827 45.7% 5 (39)

López (2012) Argentine * 1014 23.2% 7 (23)

Ezzeddin (2016) Iran * 300 8.33% 9 (25)

Ngozi (2008) Kenya * 1071 24.8% 6 (14)

Aminu (2019) Nigeria * 452 38.9% 6 (40)

Kariuki (2016) Kenya * 202 27.4% 6 (22)

Nyaruhucha (2009) Tanzania * 204 63.7% 5 (41)

Yamamoto (2019) Tanzania * 227 24.7% 5 (21)

Ugwa (2016) Nigeria * 220 17% 6 (42)

Kugbey (2021) Ghana * 214 23.8% 7 (43)

Macheka (2016) Africa * 597 54% 6 (44)

Mathee (2014) Africa * 307 22.8% 7 (45)

Adam(2005) Africa * 744 14.5% 6 (46)

Abdelgadir (2012) Sudan * 292 33.5% 5 (47)

Abubakri (2016) Africa * 578 22.8% 8 (48)

Kortei (2019) * 217 48.4% 7 (5)

Anthonia (2019) Africa * 420 62.8% 8 (19)

Gyimah (2020) Africa * 416 38.5% 6 (49)

Obse (2012) Africa * 374 41.7% 6 (50)

Nyanza (2014) Tanzania * 340 45.6% 5 (51)

Garg (2010) * 180 5% 5 (52)

Humayun (2021) Pakistan * 150 30.6% 6 (53)

Gibore (2020) Africa * 338 41.1% 8 (54)

Jonathan (2020) America * 547 2.9% 5 (55)

Kaur (2021) India * 1000 38% 5 (56)

Simpson (2000) America * 225 35% 6 (57)

Posner (1957) America * 600 1.6% 5 (32)

Wondimu (2021) Africa * 407 25.5% 8 (58)

Yoseph (2015) Africa * 605 30.5% 8 (59)

Galali (2020) Iran * 400 60.5% 7 (17)

Boadu (2018) Africa * 400 30.2% 6 (60)

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Table 2. Sensitivity Analysis for Prevalence Over 0.70

Study Effect Size 95% CI % Weight References

Posner (1957) 0.017 0.006 0.027 2.36 (32)

Geissler (1998) 0.56 0.501 0.619 2.31 (37)

Simpson (2000) 0.351 0.289 0.413 2.3 (57)

Luoba (2004) 0.457 0.423 0.491 2.35 (39)

Adam (2005) 0.145 0.12 0.17 2.35 (46)

Nyaruhucha (2009) 0.637 0.571 0.703 2.29 (41)

Garg (2010) 0.05 0.018 0.082 2.35 (52)

Mensah (2010) 0.47 0.421 0.519 2.32 (35)

Mortazavi (2010) 0.155 0.125 0.185 2.35 (24)

Young (2010) 0.379 0.359 0.399 2.36 (3)

Abdelgadir (2012) 0.336 0.281 0.39 2.31 (47)

Ahmed (2012) 0.404 0.356 0.452 2.32 (36)

López (2012) 0.232 0.206 0.258 2.35 (23)

Obse (2012) 0.417 0.367 0.467 2.32 (50)

Patil (2012) 0.341 0.298 0.385 2.33 (38)

Khoushab (2014) 0.175 0.122 0.228 2.32 (26)

Lumish (2014) 0.462 0.384 0.54 2.26 (16)

Mathee (2014) 0.228 0.181 0.275 2.33 (45)

Nyanza (2014) 0.456 0.403 0.509 2.32 (51)

Ezzeddin (2015) 0.083 0.052 0.115 2.35 (25)

Yuseph (2015) 0.304 0.267 0.341 2.34 (59)

Abubakri (2016) 0.228 0.194 0.263 2.34 (48)

kariuki (2016) 0.272 0.211 0.334 2.3 (22)

Macheka (2016) 0.541 0.501 0.581 2.34 (44)

NanaAdjei (2016) 0.1 0.062 0.137 2.34 (34)

Ugwa (2016) 0.173 0.123 0.223 2.32 (42)

Roy (2017) 0.374 0.305 0.444 2.28 (20)

Santos (2017) 0.057 0.042 0.072 2.36 (20)

Boadu (2018) 0.303 0.257 0.348 2.33 (13)

Aminu (2019) 0.389 0.344 0.434 2.33 (60)

Anthonia (2019) 0.629 0.582 0.675 2.33 (40)

kortei (2019) 0.484 0.417 0.55 2.29 (19)

Miller (2019) 0.447 0.397 0.498 2.32 (5)

Yamamoto (2019) 0.247 0.191 0.303 2.31 (1)

Galali (2020) 0.605 0.557 0.653 2.33 (21)

Gibore (2020) 0.411 0.359 0.464 2.32 (17)

Gyimah (2020) 0.385 0.338 0.431 2.33 (54)

Jonathan (2020) 0.029 0.015 0.043 2.36 (49)

Konlan (2020) 0.476 0.418 0.533 2.31 (55)

Humayun (2021) 0.307 0.233 0.38 2.27 (10)

Kaur (2021) 0.38 0.35 0.41 2.35 (53)

Kugbey (2021) 0.238 0.181 0.295 2.31 (56)

Wondimu (2021) 0.256 0.213 0.298 2.33 (43)

D+L pooled effect sizesa 0.324 0.269 0.38 100

a DerSimonian-Laird (D+L) is the simplest and most commonly used method for fitting the random effects model for meta-analysis (61).

https://www.bing.com/ck/a?!&&p=e651384f05f57e23JmltdHM9MTY3ODIzMzYwMCZpZ3VpZD0yNDM1NjZmZS1kNDU4LTY5Y2MtMmE5ZC03NDYwZDU5ZTY4ODAmaW5zaWQ9NTE0MQ&ptn=3&hsh=3&fclid=243566fe-d458-69cc-2a9d-7460d59e6880&psq=D%2bL+pooled+ES%3f&u=a1aHR0cHM6Ly9wc3ljaC51bmwuZWR1L3BzeWNycy85NDEvcTQvbWV0YV9FU18xNDEucGRm&ntb=1

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Table 3. Sensitivity Analysis for Prevalence Less Than 0.06

Study Effect Size 95% CI % Weight References

Geissler (1998) 0.56 0.501 0.619 2.36 (37)

Rainville (1998) 0.765 0.716 0.815 2.38 (33)

Simpson (2000) 0.351 0.289 0.413 2.36 (57)

Luoba (2004) 0.457 0.423 0.491 2.4 (39)

Adam (2005) 0.145 0.12 0.17 2.41 (46)

ngozi (2008) 0.74 0.714 0.767 2.41 (14)

Nyaruhucha (2009) 0.637 0.571 0.703 2.35 (41)

Mensah (2010) 0.47 0.421 0.519 2.38 (35)

Mortazavi (2010) 0.155 0.125 0.185 2.4 (24)

Young (2010) 0.379 0.359 0.399 2.41 (3)

Abdelgadir (2012) 0.336 0.281 0.39 2.37 (47)

Ahmed (2012) 0.404 0.356 0.452 2.38 (36)

López (2012) 0.232 0.206 0.258 2.41 (23)

Obse (2012) 0.417 0.367 0.467 2.38 (50)

Patil (2012) 0.341 0.298 0.385 2.39 (38)

Khoushab (2014) 0.175 0.122 0.228 2.37 (26)

Lumish (2014) 0.462 0.384 0.54 2.33 (16)

Mathee (2014) 0.228 0.181 0.275 2.38 (45)

Nyanza (2014) 0.456 0.403 0.509 2.37 (51)

Ezzeddin (2015) 0.083 0.052 0.115 2.4 (25)

Yuseph (2015) 0.304 0.267 0.341 2.4 (59)

Abubakri (2016) 0.228 0.194 0.263 2.4 (48)

kariuki (2016) 0.272 0.211 0.334 2.36 (22)

Macheka (2016) 0.541 0.501 0.581 2.39 (44)

NanaAdjei (2016) 0.1 0.062 0.137 2.4 (34)

Ugwa (2016) 0.173 0.123 0.223 2.38 (42)

Roy (2017) 0.374 0.305 0.444 2.34 (20)

Santos (2017) 0.057 0.042 0.072 2.42 (13)

Boadu (2018) 0.303 0.257 0.348 2.39 (60)

Aminu (2019) 0.389 0.344 0.434 2.39 (40)

Anthonia (2019) 0.629 0.582 0.675 2.38 (19)

kortei (2019) 0.484 0.417 0.55 2.35 (5)

Miller (2019) 0.447 0.397 0.498 2.38 (1)

Yamamoto (2019) 0.247 0.191 0.303 2.37 (21)

Galali (2020) 0.605 0.557 0.653 2.38 (17)

Gibore (2020) 0.411 0.359 0.464 2.38 (54)

Gyimah (2020) 0.385 0.338 0.431 2.38 (49)

Konlan (2020) 0.476 0.418 0.533 2.37 (10)

Humayun (2021) 0.307 0.233 0.38 2.33 (53)

Kaur (2021) 0.38 0.35 0.41 2.4 (56)

Kugbey (2021) 0.238 0.181 0.295 2.37 (43)

Wondimu (2021) 0.256 0.213 0.298 2.39 (43)

D+L pooled effect size 0.366 0.306 0.427 100

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24 studies were related to 2015 and beyond. The pooled
prevalence before 2015 was 37% (heterogeneity: I2 = 99.6%,
P = 0.001) and after 2015 was 32% (heterogeneity:
I2 = 99.2%, P = 0.001) (Figure 4).

Subgroup Analysis – Marital Status
Five studies examined the prevalence of pica in pregnancy
based on marital status. In this study, the pooled prevalence
of both married and single was 41%. The heterogeneity of
studies related to married women was I2 = 97.2%, P = 0.001
and the heterogeneity of studies related to single women
was I2 = 98.1%, P = 0.001 (Figure 5).

Subgroup Analysis – the Place of Residence
Five studies examined the prevalence in urban areas,
and four studies examined the prevalence in rural areas.
Random effect results showed a pooled prevalence of
47% and 54%, respectively. I2 test values show high
heterogeneity (I2 = 87.6%, P = 0.001 and I2 = 88%, P = 0.001)
(Figure 6).

Subgroup Analysis – Education Level
In this analysis, the level of education includes two
categories up to primary school and higher than primary
school. The overall prevalence in the first category was

40% (heterogeneity: I2 = 93.3%, P = 0.001) and in the
second category was 39% (heterogeneity: I2 = 96.9%,
P = 0.001). Three studies were discarded because of non-
compliance (25,33,34) (Figure 7).

Subgroup Analysis – Age
In this study, the age of women includes two classes under
30 years and over 30 years. The pooled prevalence was
37% (95% CI: 20%-54%) In women under 30 years and
31% (95% CI: 11%-51%) In women over 30 years. The
heterogeneity index of the studies was I2 = 97.3%, P = 0.001
and I2 = 97.9%, P = 0.0011 respectively (Figure 8).

Subgroup Analysi s– Employment Status
In this analysis, employment status includes two categories
of employed and non-employed. The pooled prevalence
in four studies with employed women was 29% (95% CI:
3%-55%) and in three studies with unemployed women
was 39% (95% CI: -6-84%). The heterogeneity index of the
studies was I2 = 98.4%, P = 0.001 and I2 = 99.4%, P = 0.001,
respectively (Figure 9).

Subgroup Analysis – a Geographical Region
This study covers regions such as Africa, the Americas,
and Asia. The overall prevalence in African countries

Figure 3. The Pooled Prevalence of Pica in Pregnancy (Pica Type). Figure 4. The Pooled Prevalence of Pica in Pregnancy (Year of Study).

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is 38% (I2 = 98.5, P = 0.001), American 32% (I2 = 99.5,
P = 0.001), and Asian 28% (I2 = 98.9, P = 0.001) (Figure 10).

Subgroup analysis – Trimester of Pregnancy
The total prevalence of pica in the first trimester of
pregnancy (0-14 weekly ) is 41% (I2 = 99.2%, P = 0.001),
in the second trimester of pregnancy (14-28 weekly)
19% (I2 = 98.6%, P = 0.001), and the third trimester of
pregnancy (Over 28 weeks) 17% (I2 = 98.8%, P = 0.001)
(Figure 11).

Subgroup Analysis – Parity
The pooled prevalence in the seven studies related
to nulliparous women (women without a history of
childbirth) was 32% (95% CI: 17%-47%). The pooled
prevalence in the four studies related to multiparous
women (women with a history of childbirth) was 34%
(95% CI: 5%-63%). The heterogeneity of each category
was significant (I2 = 97.5%, P = 0.001 and I2 = 98.7%,
P = 0.001) (Figure 12).

Discussion
Pica during pregnancy is a health problem worldwide.

Figure 5. The Pooled Prevalence of Pica in Pregnancy (Marital Status).

Figure 7. The Pooled Prevalence of Pica in Pregnancy (Educational Status).

Figure 8. The Pooled Prevalence of Pica in Pregnancy (Women’s Age).

Figure 6. The Pooled Prevalence of Pica in Pregnancy (Place of Residence).

Because on the one hand, Pica prevents the delivery of
micronutrients to the mother by disturbing the nutritional
balance, and on the other hand, it causes problems for the
mother and child because of the consumption of harmful
substances (62).

In this review, the global prevalence of pica in pregnancy
was 34%. This amount is higher than the overall prevalence
of the Fawcett study (27.8%) (28). Also, the total prevalence
of pica and geophagy is higher than amylophagy. These
results were similar to the results of the other eight studies
(17,22,33,35,36,63,64) and different from the results of the
other three studies ((32,65,66). The pleasant appearance
and smell of soil-derived materials are the reason for the
greater prevalence of geophagy. Yang’s study hypothesizes
that higher consumption of geophagy is because of its
palliative effect on gastrointestinal disorders such as
gastric reflux, which is more common in pregnancy (65).
There is also a close relationship between pagophagia and

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anemia, which is a risk factor for Pica behavior (25).
However, the pooled prevalence of pica in pregnancy

has decreased since 2015. Mathee and colleagues’ study
showed similar findings (45). One possible reason is
that most post-2015 studies are in African countries
where non-nutritious consumption is traditionally and
culturally acceptable, so the pica report in these countries
is less-than reality. Pica, on the other hand, is a protected
social behavior that women refuse to express to avoid
criticism from others (28,45). These reasons justify the

Figure 9. The Pooled Prevalence of Pica in Pregnancy (Employment Status).

Figure 11. The Pooled Prevalence of Pica in Pregnancy (Trimester of
Pregnancy).

Figure 12. The Pooled Prevalence of Pica in Pregnancy (Parity).

Figure 10. The Pooled Prevalence of Pica in Pregnancy (Geographical
Region).

lower prevalence of pica after 2015.
Education, empowerment (financial, educational, social,

etc), and distribution of dietary supplements reduce pica
in women (10,25,67). Therefore, it is recommended to
implement educational programs, empower women and
distribute nutritional supplements during pregnancy.

The pooled prevalence was the same in married and
single women. This finding was similar to the results of
Yang’s study (65) and different from the findings of the
previous four studies (10,22,23,33).

According to this study, the overall prevalence of
pica was higher in rural than in urban women. Three
studies have shown the same results (10,17,35). Rural
communities are likely to be in a lower position in terms
of social statuses, such as education level and poverty,
which, according to studies, these factors have a positive
effect on Pica practice (68).

The results showed that the prevalence of pica was

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higher in women with primary education. Our results were
similar to the findings of five studies (17,21,22,35,45) and
different from the findings of three studies (10,20,23). In
educated women, due to high health literacy, consumption
of non-nutrient is less (10).

According to the findings, the prevalence of pica is
higher in women under 30 years of age. Five studies
showed the same results (10,17,22,25,45). Because young
women are probably still growing, their bodies need more
iron. Studies show that there is a positive association
between iron deficiency and pica (16).

Also, the overall prevalence of pica is higher in
unemployed women than in employed women. These
findings were matched to the results of the Galali study
(17) and contradict the findings of the previous two
studies (24,25). Unemployed people are at a lower level in
terms of social status, and according to Khosravizadegan
and colleagues’ study, pica is more common in people
with low social classes (69).

The prevalence of pica in Asian countries was lower than
the global average. Because more than half of the articles
in this meta-analysis are related to African countries with
high poverty and malnutrition, Asian studies in this meta-
analysis are related to developing countries that have
provided good supplements and diet plans for pregnant
women (70). Another reason is the high level of education
of Asian women. For example, in one Asian study, 76%
of women had an academic education (25). Higher
education is associated with increased awareness of the
negative consequences of pica. These women also report
less pica behavior due to shame (28).

According to this meta-analysis, the highest prevalence
of pica was in the first trimester of pregnancy. These
findings are similar to the results of the other six studies
(10,17,23-25,71) and contradictory to the findings of the
Geissler et al study (37). Higher levels of human chorionic
gonadotropin in the first trimester of pregnancy lead to
an increase in the prevalence of pica. An increase in this
hormone causes pregnancy nausea and vomiting and
changes in the sense of smell and taste (41,72). Therefore,
women are more inclined to eat non-nutritious foods
to relieve nausea during pregnancy and because of the
pleasant and excellent smell of non-nutrient (10).

According to this meta-analysis, the highest prevalence
of pica was in multiparous women. These findings are
similar to the results of the previous two studies (17,21)
and contradictory to the findings of the three studies
(16,22,25).

Although pica is present in all communities, its
prevalence has decreased since 2015. A possible reason is
the lack of reporting and cultural and ethnic traditions. It
is suggested that the effects of these factors be investigated
in future studies.

Strengths and Limitations
Use of studies published in recent years, assessment of the

prevalence of pica in subgroups (based on marital status,
place of residence, level of education, age, geographical
area, trimester of pregnancy, and parity), use high-quality
studies in the meta-analysis, and evaluation of publication
bias of studies (Begg test and sensitivity analysis) were the
strengths of this study.

The most important limitation was the lack of a valid
scale for Pica evaluation. It is suggested that a scale be
developed in future studies to evaluate pica. Another
limitation of this study is the plurality of studies in African
countries whose high poverty and specific culture affect
the prevalence of pica in pregnancy. Another limitation
is the lack of quality studies in European countries.
Therefore, the results should be generalized with caution.

Conclusions
According to the current meta-analysis, the prevalence
of pica in pregnancy was 34%. Given the scattering of
studies worldwide, the results of this study are acceptable.
Also, the meta-analysis findings support a decrease in
the prevalence of pica after 2015. These rates were higher
for married women, rural women, less educated women,
younger women, unemployed women, African women,
women in the first trimester, and multiparous women.
Therefore, the development of screening programs
and training for these high-risk groups can reduce the
prevalence of pica.

Authors’ Contribution
SHSA and AAF were responsible for all stages of literature search and
extraction. MRMS did the analysis. SHSA prepared the initial draft of the
article. The comments of the other two authors were applied in the final
draft. The final version was read and confirmed by all 3 people.

Conflict of Interests
Authors declare that they have no conflict of interests.

Ethical Issues
This study was approved by the ethical committee of Shahroud
University of Medical Sciences (No. IR.SHMU.REC.1400.184).

Acknowledgments
We thank Shahroud of Medical Sciences for the support provided for
this research project References.

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