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Research Article
Eur Addict Res 2023;29:19–29
Morbidity through 3 Years of Age in Children
of Women Using Methamphetamine during
Pregnancy: A National Registry Study
Roman Gabrhelík
a, b Svetlana Skurtveit
c, d Blanka Nechanská
a Viktor Mravčík
a
Marte Handal
a, c
aDepartment of Addictology, First Faculty of Medicine, Charles University, Prague, Czech Republic; bDepartment of
Addictology, General University Hospital in Prague, Prague, Czech Republic; cNorwegian Institute of Public Health,
Oslo, Norway; dNorwegian Centre for Addiction Research at the University of Oslo, Oslo, Norway
Received: February 15, 2022
Accepted: August 26, 2022
Published online: November 24, 2022
Correspondence to:
Roman Gabrhelík, roman.gabrhelik @ lf1.cuni.cz
© 2022 The Author(s).
Published by S. Karger AG, Basel
Karger@karger.com
www.karger.com/ear
DOI: 10.1159/000527238
Keywords
Prenatal exposure · Methamphetamine · Health registries ·
Child morbidity · Long-term effects · Hospitalization
Abstract
Background: There is a lack of studies on methamphet-
amine (MA) exposure and morbidity in children beyond the
perinatal period. Objectives: We compared morbidity in
children (0–3 years) with prenatal MA exposure to opioid-
exposed and to non-exposed children. Methods: We used
data from a Czech nationwide, registry-based cohort study
(2000–2014). Children, who reached 3 years of age, of moth-
ers hospitalized with (i) MA use disorder during pregnancy
(MA; n = 194), (ii) opioid use disorder during pregnancy (opi-
oids; n = 166), and (iii) general population (GP; n = 1,294,349)
with no recorded history of substance use disorder (SUD).
Information on inpatient contacts, length of stay, and diag-
noses (International Statistical Classification of Diseases and
Related Health Problems 10th Revision [ICD-10]) were as-
sessed. Crude and adjusted odds ratios (aOR), 95% confi-
dence interval (CI) for the risk of hospitalization, and for get-
ting diagnosis from the ICD-10 diagnosis chapters were cal-
culated using binary logistic regression. A stratified analysis
on hospitalizations with SUD of mothers was performed. Re-
sults: No significant differences were found in the measures
of hospitalization between the MA and opioid groups. Chil-
dren prenatally exposed to MA and opioids had higher num-
bers of hospitalizations and diagnoses and longer stays in
hospital than children in the GP. Increased risks of certain
infectious and parasitic diseases were found in both MA (aOR
= 1.6; CI: 1.1–2.3) and opioid (aOR = 1.9; 1.3–2.8) groups as
compared to the GP group. The most pronounced difference
in stratified analysis on maternal hospitalizations related to
SUD after birth was observed for injury, poisoning, and cer-
tain other consequences of external causes in the strata of
the MA group who had hospitalized mothers (aOR 6.3, 1.6–
24.6) compared to the strata without maternal hospitaliza-
tions (aOR 1.4, 0.9–2.3). Conclusion: This study suggests that
children born to mothers using MA during pregnancy have
similar morbidity during the first 3 years of life but higher
than the GP. The excess of risk was primarily due to infections
and injuries in the MA group. © 2022 The Author(s).
Published by S. Karger AG, Basel
This article is licensed under the Creative Commons Attribution 4.0
International License (CC BY) (http://www.karger.com/Services/
OpenAccessLicense). Usage, derivative works and distribution are
permitted provided that proper credit is given to the author and the
original publisher.
Gabrhelík/Skurtveit/Nechanská/Mravčík/
Handal
Eur Addict Res 2023;29:19–29
20
DOI: 10.1159/000527238
Introduction
Methamphetamine hydrochloride (MA) use during
pregnancy is increasingly common [1–3]. A considerable
proportion of women do not seem to curb their MA use
during pregnancy [4] despite the possible increased risk
of adverse perinatal, neonatal, and childhood outcomes
[5].
A limited number of studies analysed the association
between prenatal MA exposure and the child’s develop-
mental outcomes beyond the perinatal period [6–10], and
a majority focused primarily on behavioural, cognitive,
and social problems in the children. The most rigorous
study to date is the longitudinal Infant Development, En-
vironment and Lifestyle(IDEAL) study in which 204 chil-
dren with prenatal MA exposure and 208 unexposed were
followed from delivery through childhood [11, 12]. This
study did not find any associations between prenatal MA
exposure and mental or psychomotor development in
children at one, two, and 3 years of age [13]. In the MA-
exposed children, only a subtle adverse effect on fine mo-
tor performance was observed at the age of one year, but
this vanished in three-year-olds [13].
Although knowledge about long-term outcomes of
prenatal exposure to illicit drugs is limited, an increas-
ing number of studies report on the influence of factors
such as drug-related lifestyle (e.g., relative poverty) on
child outcomes [14–16]. However, no study has report-
ed on the child’s health condition requiring hospitaliza-
tion beyond the perinatal period after prenatal MA ex-
posure.
The aim of this study was to examine morbidity during
the first 3 years of life among children with prenatal MA
exposure. Specifically, we compared these children with
children prenatally exposed to opioids as an attempt to
control for unmeasured confounding since pregnant
women using MA and those using opioids share similar
background characteristics regarding socio-economic
and lifestyle factors [16, 17]. This comparison also allows
us to study whether the different substances used by the
mother played an important role in the morbidity of chil-
dren. Both groups were also compared to children of
mothers from the general population (GP), i.e., without
diagnosed substance use disorders (SUD) to study if there
is any difference in the prevalence of morbidity between
the two substance exposed groups and the unexposed.
Based on our earlier results [17] showing worse neonatal
outcomes in the opioid-exposed group than in the MA-
exposed group, we hypothesized that the opioid-exposed
children would have greater morbidity than children in
the MA group. In addition, children from both the opioid
and the MA groups would have a higher number of hos-
pitalizations and increased morbidity than children from
the GP.
Methods
We linked data from Czech national health registries using the
personal identification numbers [18] to investigate inpatient child
morbidity.
Data Sources
In Czechia, physicians are obligated by law to report data to the
national health registries. The National Register of Reproduction
Health (NRRH) holds information about maternal health; lifestyle
during pregnancy; demographic and socio-economics; and infor-
mation about delivery and the neonate, including birth parame-
ters, congenital malformations, and death. The National Register
of Addiction Treatment (NRAT) includes information about pa-
tients who receive opioids as addiction medication, e.g., date of
initiation and termination of treatment and type of opioid.
The National Register of Inpatient Treatment (NRIT) provides
information on all single hospitalization episodes, including dates
of admission, discharge from hospital, and transfer to another de-
partment within the same hospital stay. The International Statisti-
cal Classification of Diseases and Related Health Problems 10th
Revision (ICD-10) diagnostic codes were used in the discharge
summary.
Hospitals represent the secondary healthcare level. The prima-
ry level is represented by the general practitioners for children and
adolescents, and each child is registered to one specific general
practitioner. The general practitioners must refer patients to the
inpatient treatment. Outpatient emergency units in hospitals refer
patients to inpatient departments. Nearly all hospitals have paedi-
atric departments that provide acute care. The NRIT does not have
information on patients who are only in contact with primary
healthcare services. The Information System on Deaths (ISZEM)
is a general mortality register providing records on time and cause
of death for persons with a permanent or long-term residence in
Czechia.
Women Using MA during Pregnancy and Their Children
The start and end of pregnancy data were retrieved from the
NRRH. Pregnant women who were hospitalized and diagnosed
with mental and behavioural disorders due to use of other stimu-
lants (ICD-10 code F15; all sub-codes registered in the NRIT) dur-
ing pregnancy were defined as women using MA during pregnan-
cy since this diagnostic group is nearly exclusively represented by
MA in Czechia (Fig.1) [19, 20]. The diagnosis should reflect a rel-
evant health problem of the patient for the actual hospital stay.
Thus, to receive a F15 diagnosis during pregnancy, the woman
should have used psychostimulants in pregnancy. Aside from less
than 1% (n = 2) with an acute intoxication diagnosis, nearly all
women in the MA group had a diagnosis indicating prolonged use.
We excluded women hospitalized with two or more diagnoses re-
lated to different psychoactive substances (F10-F18) and women
who were hospitalized for polydrug use (F19) before or during
pregnancy in the study period to reduce the problem of polysub-
Morbidity in Methamphetamine-Exposed
Children
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Eur Addict Res 2023;29:19–29
DOI: 10.1159/000527238
stance use (Fig.1). Children born to women with a diagnosis indi-
cating MA use during pregnancy formed the MA group. All chil-
dren in this group were from single births.
Women Using Opioids during Pregnancy and Their Children
Women using opioids during pregnancy were defined as those
hospitalized with a diagnosis of mental or behavioural disorder
due to opioid use (ICD-10 code F11; all sub-codes) [14]. Children
born to women with a diagnosis indicating opioid use during preg-
nancy formed the prenatal opioid group. All children in this group
were from single births (Fig.1).
Women without Indications of SUD and Their Children
Women who were not diagnosed with any mental and behav-
ioural disorders due to psychoactive substance use (ICD-10 codes
F10-F19; all sub-codes) prior to or during pregnancy were defined
Fig. 1. Flowchart on construction of cohorts of women and their
children included in the study. Women-level identification. We
identified women using MA and opioids during pregnancy and
their children. The start and end of pregnancy data were retrieved
from the National Register of Reproduction Health. Pregnant
women who were hospitalized and diagnosed with mental and be-
havioural disorders due to use of other stimulants (ICD-10 code
F15; all sub-codes registered in the National Register of Inpatient
Treatment) during pregnancy were defined as women using MA
during pregnancy. Women using opioids during pregnancy were
defined as those hospitalized with a diagnosis of mental or behav-
ioural disorder due to opioid use (ICD-10 code F11; all sub-codes).
Children born to women with a diagnosis indicating opioid use
during pregnancy formed the prenatal opioid group. Women us-
ing MA during pregnancy and women from the prenatal opioid
group who were hospitalized with two or more diagnoses related
to other psychoactive substances (ICD-10 codes F10-F19) before
or during pregnancy were excluded. Women who were not diag-
nosed with any mental and behavioural disorders due to psychoac-
tive substance use (ICD-10 codes F10-F19; all sub-codes) prior to
or during pregnancy were defined as the GP of women who had
no history of drug use (GP group). Women from the GP group
who had a history any ICD-10 F10-F19 diagnose before or during
pregnancy were excluded. Child-level identification: in all three
groups, children from multiple births were excluded from the
analysis. In all three groups, we also excluded (i) stillbirth; (ii) chil-
dren who did not reach age of three years; (iii) children who died
before the age of three years. Children who remained were includ-
ed in the study.
Gabrhelík/Skurtveit/Nechanská/Mravčík/
Handal
Eur Addict Res 2023;29:19–29
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DOI: 10.1159/000527238
as the GP of women who had no history of drug use (GP group).
Children from multiple births were excluded from the analysis
(Fig.1).
Outcomes
Hospitalizations were chosen as the measure of morbidity. In-
formation about hospitalizations of children was assessed for the
time period from discharge from the hospital after birth until the
age of three years. Data on all inpatient contacts from NRIT were
used to assess information about length of stay and primary and
secondary ICD-10 diagnoses (chapter level I–XXI) at discharge.
Study Population and Study Period
The study population consisted of all children born in single
births in Czechia during the study period, 2000–2014. Of these,
261 were children in the MA group and 197 were in the opioid
group. Children of women from the GP with no recorded history
of SUD formed the largest group (N = 1,495,370). Children who
were born close to the end of the study period and therefore did
not reach 3 years of age were excluded (Fig.1). Also excluded were
children who died before the age of three years (N = 2 [0.8%] in the
MA group, N = 1 [0.5%] in the opioid group, and N = 845 [0.1%]
in the GP group). The final study population consisted of 194 chil-
dren in the MA group, 166 in the opioid group, and 1,294,349 in
the GP group.
Maternal Background Variables
Background characteristics of the pregnant women, such as age,
marital status, education, previous abortions, smoking, and alcohol
use during pregnancy, were obtained from the NRRH as described
Table 1. Socio-economic, drug use, and healthcare-related characteristics of pregnant women in Czechia, 2000–2014
MA users (n = 194) Opioid users (n = 166) GP (n = 1,294,349)
n% 95% CI n% 95% CI n% 95% CI
Age, years
≤24 103 53.1 45.8–60.2 80 48.2 40.4–56.0 268,880 20.8 20.7–20.8
25–29 63 32.5 26.0–39.6 51 30.7 23.9–38.4 484,794 37.5 37.4–37.5
30–34 24 12.4 8.2–18.0 30 18.1 12.7–25.0 387,040 29.9 29.8–30.0
≥35 3 1.5 0.4–4.8 5 3.0 1.1–7.3 142,730 11.0 11.0–11.1
Marital status
Not married 165 85.1 79.1–89.6 133 80.1 73.1–85.7 411,820 31.8 31.7–31.9
Married 25 12.9 8.7–18.6 27 16.3 11.2–23.0 853,567 65.9 65.9–66.0
Unknown 3 1.5 0.4–4.8 6 3.6 1.5–8.1 18,057 1.4 1.4–1.4
Education
Primary 109 56.2 48.9–63.2 92 55.4 47.4–63.1 138,703 10.7 10.7–10.8
Secondary 76 39.2 32.3–46.5 67 40.4 32.9–48.3 877,972 67.8 67.8–67.9
Tertiary 0 0.0 0.0–1.9 2 1.2 0.2–4.7 207,414 16.0 16.0–16.1
Unknown 8 4.1 1.9–8.3 5 3.0 1.1–7.3 59,355 4.6 4.5–4.6
Abortions
Induced 47 24.2 18.5–31.0 39 23.5 17.4–30.8 165,759 12.8 12.7–12.9
Spontaneous 25 12.9 8.7–18.6 21 12.7 8.2–18.9 191,144 14.8 14.7–14.8
Using other substances during pregnancy
Alcohol (misuse) 6 3.1 1.3–6.9 10 6.0 3.1–11.1 1,533 0.1 0.1–0.1
Smoking 82 42.3 35.3–49.6 68 41.0 33.5–48.9 74,531 5.8 5.7–5.8
Deliveries by multiplicity
Single 188 96.9 93.1–98.7 160 96.4 91.9–98.5 1,270,180 98.1 98.1–98.2
Twins and more 6 3.1 1.3–6.9 6 3.6 1.5–8.1 24,169 1.9 1.8–1.9
mean SD mean SD mean SD
Start of prenatal care (weeks) 12.7 9.0 11.7 8.2 10.3 3.9
Medical controls, n7.0 5.4 6.8 4.9 11.4 3.6
MA users – women hospitalized with a diagnosis of mental or behavioural disorder due to use of amphetamines (ICD-10 code F15, all
sub-codes) during pregnancy. Opioid users – women hospitalized with a diagnosis of mental or behavioural disorder due to opioid use
(ICD-10 code F11, all sub-codes) during pregnancy. GP – women who had no history of drug use defined as women who were not diagnosed
with any of mental and behavioural disorders due to psychoactive substance use (ICD-10 codes F10-F19; all sub-codes) prior or during
pregnancy. Education primary – consists of nine grades. Education secondary – 2- or 3-year course (vocational school) or 4-year course
(professional school and lyceum). Education tertiary – higher professional school and university. CI, confidence interval.
Morbidity in Methamphetamine-Exposed
Children
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Eur Addict Res 2023;29:19–29
DOI: 10.1159/000527238
previously (18). These variables were chosen based on the literature
suggesting the negative effect on birth outcomes and later child de-
velopment [21–23]. We also used information on start of prenatal
care and the number of medical controls during pregnancy as a
proxy of lifestyle and health literacy characteristics [14, 16].
Analysis Strategy and Statistics
Descriptive statistics (mean, median, and interquartile range)
were used to present the proportion of hospitalized children, fre-
quency of hospitalizations, length of hospital stay, and number of
diagnoses (primary and secondary diagnosis) per child in each
group who reached 3 years of age. Unadjusted and adjusted odds
ratios (aOR) with 95% confidence interval (CI) for the risk of hos-
pitalization were calculated by binary logistic regression and pre-
sented for the MA group compared to the opioid group and the
MA and opioid group compared to the GP. Negative binomial re-
gression analysis was used to calculate differences between groups
in number of hospitalizations, length of stay, and number of diag-
noses.
We then calculated the proportion of children hospitalized
with different ICD-10 diagnoses during the period after discharge
following birth until the age of 3 years. The population of children
who reached 3 years of age was used as the denominator. CI for
proportion was calculated using the continuity correlated score
interval method (20). To control for relevant maternal background
characteristics, we performed separate binary logistic regression
for the categorical dependent variables (diagnoses yes/no) for each
diagnosis chapter. Unadjusted and aOR with 95% CI were pre-
sented for the MA group compared to the opioid group and for the
MA and opioid group compared to the GP. Significant results from
the unadjusted analyses were adjusted for maternal age, marital
status, education, smoking, alcohol use, and number of medical
controls during pregnancy.
We also performed stratified analyses on (i) severe maternal
substance use during the first 3 years after birth (yes/no) defined
as a maternal hospitalization with an ICD-10 F10-F19 diagnosis
within the child’s first 3 years of life; (ii) premature birth (yes/no);
and (iii) small for gestational age (yes/no).
The level of statistical significance for all analyses was set at p <
0.05 using 2-tailed comparisons. Statistical analyses were conduct-
ed using SPSS for Windows version 23 and Stata 14.
Results
Maternal Background Characteristics
Women from the MA group were younger and more
frequently married compared to women from the opioid
group (Table1). As opposed to the GP group, both drug-
related groups were younger, and most were not married.
Among both MA and opioid users, more than half had
only a primary education and a large proportion had pre-
viously had an induced abortion. The smoking preva-
lence was high in both drug-related groups. MA-using
women started prenatal care two and a half weeks later
and had fewer medical controls during pregnancy than
those in the GP group.
Table 2. Hospital admissions in children (0–3 years) of women hospitalized with a diagnosis of mental or behavioural disorder in MA, opioid, and general population (GP)
groups in Czechia, 2000–2014
MA Opioids MA versus opioids
(reference)
GP MA versus GP
(reference)a
Opioids versus GP
(reference)a
Children who reached age of 3 years, n194 166 1,294,349
OR (95% CI) OR (95% CI) OR (95% CI)
Hospitalized children, n (%, CI) 92 (47.4; 40.3–54.7) 88 (53.0; 45.1–60.7) 0.8 (0.5–1.2) 456,207 (35.2; 35.2–35.3) 1.7 (1.3–2.2) 2.1 (1.5–2.8)
aOR (95% CI) 0.8 (0.5–1.2) aOR (95% CI) 1.2 (0.9–1.6) aOR (95% CI) 1.5 (1.1-2.0)
p p p
Number of hospitalizations, mean, median, IQR 2.1, 1.0, 1.0–3.0 2.4, 2.0, 1.0–3.0 0.288 1.8, 1.0, 1.0–2.0 0.020 <0.001
Length of stay in days, mean, median, IQR 15.1, 7.0, 4.0–17.0 18.1, 11.5, 4.0–23.5 0.241 8.4, 4.0, 2.0–8.0 <0.001 <0.001
Number of all diagnoses mean, median, IQR 4.1, 3.0, 2.0–5.0 4.7, 3.0, 2.0–6.0 0.185 3.0, 2.0, 1.0–4.0 <0.001 <0.001
Excluded: ICD-10 codes Z37 and Z38 diagnoses and birth hospitalization. MA – children of women hospitalized with a diagnosis of mental or behavioural disorder due to other stimulant use (ICD-10 code F15, all sub-
codes) during pregnancy. Opioids – children of women hospitalized with a diagnosis of mental or behavioural disorder due to opioid use (ICD-10 code F11, all sub-codes) during pregnancy. GP – children of women who
had no history of drug use defined as women who were not diagnosed with any of mental and behavioural disorders due to psychoactive substance use (ICD-10 codes F10-F19; all sub-codes) prior or during pregnancy.
OR (95% CI) – odds ratios (ORs) from binary logistic regression of the child being hospitalized. We compared the MA and opioid groups, and the opioid group was the reference group. In the comparison between MA or
opioid group with the GP, the GP was the reference group. aOR (95% CI) – adjusted odds ratios (ORs) for maternal age, education, smoking status during pregnancy, alcohol, and number of control. p – p value from nega-
tive binomial regression analyses. Cl, confidence interval. IQR, interquartile range.
Gabrhelík/Skurtveit/Nechanská/Mravčík/
Handal
Eur Addict Res 2023;29:19–29
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DOI: 10.1159/000527238
Table 3. Binary logistic regression comparing children (0–3 years) of women hospitalized with a diagnosis of mental or behavioural disorder in methamphetamine (MA),
opioid, and general population (GP) groups in Czechia
Chapter of ICD-10 diagnoses MA
(n = 194)
Opioids
(n = 166)
GP
(n = 1,294,349)
MA versus opioids
(reference)
MA versus GP
(reference)
Opioids versus GP (reference)
cases
n (%)
cases
n (%)
cases
n (%)
OR unadjusted
(95% CI)
OR unadjusted
(95% CI)
aOR
(95% CI)
OR unadjusted
(95% CI)
aOR
(95% CI)
I. Certain infectious and parasitic diseases (A00-B99) 36 (18.6) 37 (22.3) 114,133 (8.8) 0.8 (0.5–1.3) 2.4 (1.6–3.4) 1.5 (1.0–2.2) 3.0 (2.1–4.3) 1.9 (1.3–2.8)
III. Diseases of the blood and blood-forming organs and certain disorders involving the
immune mechanisms (D50-D89) 9 (4.6) 12 (7.2) 34,907 (2.7) 0.6 (0.3–1.5) 1.8 (0.9–3.4) 2.8 (1.6–5.1)
IV. Endocrine, nutritional, and metabolic diseases (E00-E90) 13 (6.7) 13 (7.8) 52,978 (4.1) 0.8 (0.4–1.9) 1.7 (1.0–3.0) 2.0 (1.1–3.5)
VII. Diseases of the eye and adnexa (H00-H59) 7 (3.6) 7 (4.2) 18,408 (1.4) 0.9 (0.3–2.5) 2.6 (1.2–5.5) 3.1 (1.4–6.5)
VIII. Diseases of the ear and mastoid process (H60-H95) 14 (7.2) 6 (3.6) 27,758 (2.1) 2.1 (0.8–5.5) 3.5 (2.1–6.1) 1.9 (1.1–3.4) 1.7 (0.8–3.9)
X. Diseases of the respiratory system (J00-J99) 47 (24.2) 44 (26.5) 207,153 (16.0) 0.9 (0.6–1.4) 1.7 (1.2–2.3) 1.9 (1.3–2.7)
XI. Diseases of the digestive system (K00-K93) 19 (9.8) 22 (13.3) 78,546 (6.1) 0.7 (0.4–1.4) 1.7 (1.0–2.7) 2.4 (1.5–3.7) 1.5 (1.0–2.4)
XII. Diseases of the skin and subcutaneous tissue (L00-L99) 8 (4.1) 5 (3.0) 36,147 (2.8) 0.7 (0.3–1.7) 1.5 (0.7–3.0) 2.2 (1.2–4.2)
XIV. Diseases of the genitourinary system (N00-N99) 7 (3.6) 8 (4.8) 46,102 (3.6) 0.7 (0.3–2.1) 1.0 (0.5–2.2) 1.4 (0.7–2.8)
XVI. Certain conditions originating in the perinatal period (P00-P96) 15 (7.7) 20 (12.0) 35,721 (2.8) 0.6 (0.3–1.2) 3.0 (1.7–5.0) 1.8 (1.0–3.0) 4.8 (3.0–7.7) 1.8 (1.7–4.5)
XVII. Congenital malformations, deformations, and chromosomal abnormalities (Q00-Q99) 8 (4.1) 14 (8.4) 44,362 (3.4) 0.5 (0.2–1.1) 1.2 (0.6–2.5) 2.6 (1.5–4.5) 1.9 (1.1–3.3)
XVIII. Symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere
classified (R00-R99) 24 (12.4) 25 (15.1) 122,504 (9.5) 0.8 (0.4–1.5) 1.4 (0.9–2.1) 1.7 (1.1–2.6)
XIX. Injury, poisoning, and certain other consequences of external causes (S00-T98) 23 (11.9) 12 (7.2) 82,637 (6.4) 1.7 (0.8–3.6) 2.0 (1.3–3.0) 1.6 (1.1–2.5) 1.1 (0.6–2.1)
XXI. Factors influencing health status and contact with health services (Z00-Z99) 18 (9.3) 22 (13.3) 58,730 (4.5) 0.7 (0.3–1.3) 2.2 (1.3–3.5) 3.2 (2.1–5.0) 2.3 (1.5–3.6)
MA – children of women hospitalized with a diagnosis of mental or behavioural disorder due to MA use (ICD-10 code F15, all sub-codes) during pregnancy. Opioids – children of women hospitalized with a diagnosis
of mental or behavioural disorder due to opioid use (ICD-10 code F11, all sub-codes) during pregnancy. GP – children of women who had no history of drug use defined as women who were not diagnosed with any of
mental and behavioural disorders due to psychoactive substance use (ICD-10 codes F10-F19; all sub-codes) prior or during pregnancy. OR 95% CI – odds ratio with 95% confidence interval. Reference – in the binary logistic
regression, when we comparing the MA and opioid groups, the opioid group was the reference group. In the comparison between MA or opioid group with the GP, the GP was the reference group. OR adjusted (95% CI)
– aOR for maternal age, education, smoking status during pregnancy, alcohol, and number of control. Analyses were only performed for significant results from the first adjusted analysis.
Morbidity in Methamphetamine-Exposed
Children
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DOI: 10.1159/000527238
Hospitalization of Children
By the age of 3 years, 47.4% of children from the MA
group and 53.0% of children from the opioid group had
been hospitalized at least once, compared to 35.2% of
children in the GP (Table2). Children from both drug-
related groups had higher numbers of hospitalizations
and diagnoses and longer stays in hospital than children
in the GP. Children in the MA group had slightly better,
but not significant, outcomes as opposed to children from
the opioid group regarding the number of hospitaliza-
tions, diagnoses, and length of stay.
After adjustment, the odds ratio (OR) of hospitaliza-
tion was neither significant for the comparison between
the MA and opioid group nor of the MA group versus the
GP. Comparison between the opioid group and the GP
was significant (aOR = 1.5; 95% CI: 1.1–2.0).
Children’s Diagnosis
Table3 shows the proportions of children in the dif-
ferent groups based on the different diagnoses received
until the age of three years. The most prevalent ICD-10
diagnostic chapters were chapters X Respiratory diseases
(24.2% and 26.5%) and I Infections (18.6% and 22.3%) in
the MA and the opioid groups, respectively. These two
chapters were also among the most prevalent in the GP.
The proportion of children with injury and poisoning
(Chapter XIX) was 11.9% in the MA group; of these, 65%
(n = 15) had head injuries (category S00-S09).
The unadjusted logistic regression analysis showed no
statistically significant differences in the diagnostic chap-
ters between the MA and the opioid groups (Table3). In
the unadjusted analysis when comparing the MA group
to the GP, there were differences in risk for more than half
of the diagnostic chapters. After the adjustment, the in-
creased OR remained significant for certain infectious
and parasitic diseases (aOR = 1.5; 1.0–2.2); diseases of the
ear and mastoid process (aOR = 1.9; 1.1–3.4); certain con-
ditions originating in the prenatal period (aOR = 1.8; 1.0–
3.0); and injury, poisoning, and certain other conse-
quences of external causes (aOR = 1.6; 1.1–2.5). Also, in
Table 4. Binary logistic regression comparing children (0–3 years) of women hospitalized with a diagnosis of mental or behavioural disorder
in methamphetamine (MA), opioid, and general population (GP) groups in Czechia, stratified on hospitalization (yes/no) of mother for
F10-F19 during the first 3 years after childbirth
Chapter of ICD-10 diagnoses Maternal hospitalization due to MA use after birth
yes no
n = 11 (MA), n = 1,492 (GP) n = 182 (MA), n = 1,281,952 (GP)
OR adjusted (95% CI) OR adjusted (95% CI)
I. Certain infectious and parasitic diseases (A00-B99) 3.5 (0.9–13.3) 1.4 (1.0–2.1)
VIII. Diseases of the ear and mastoid process (H60-H95) 4.6 (0.5–44.2) 1.9 (1.1–3.4)
XVI. Certain conditions originating in the perinatal period (P00-P96) 2.4 (0.3–20.5) 1.7 (1.0–3.0)
XIX. Injury, poisoning, and certain other consequences of external causes (S00-T98) 6.3 (1.6–24.6) 1.4 (0.9–2.3)
Maternal hospitalization due to opioid use after birth
yes no
n = 4 (opioids), n = 1,492 (GP) n = 162 (opioids), n = 1,281,952 (GP)
OR adjusted (95% CI) OR adjusted (95% CI)
I. Certain infectious and parasitic diseases (A00-B99) 1.4 (0.1–13.8) 1.9 (1.3–2.8)
XVI. Certain conditions originating in the perinatal period (P00-P96) 5.7 (0.5–65.6) 2.7 (1.7–4.4)
XVII. Congenital malformations, deformations, and chromosomal abnormalities
(Q00-Q99)
6.3 (0.6–69.5) 1.8 (1.0–3.2)
XXI. Factors influencing health status and contact with health services (Z00-Z99) 4.6 (0.4–48.3) 2.2 (1.4–3.5)
MA – children of women hospitalized with a diagnosis of mental or behavioural disorder due to MA use (ICD-10 code F15, all sub-codes) during pregnancy.
Opioids – children of women hospitalized with a diagnosis of mental or behavioural disorder due to opioid use (ICD-10 code F11, all sub-codes) during
pregnancy. GP – children of women who had no history of drug use defined as women who were not diagnosed with any of mental and behavioural disorders
due to psychoactive substance use (ICD-10 codes F10-F19; all subcodes) prior or during pregnancy. OR 95% CI – odds ratio with 95% confidence interval. OR
adjusted (95% CI) – in the binary logistic regression, when we compared the MA or opioid groups with the GP, the GP was the reference group. Adjusted for
maternal age, education, and smoking status during pregnancy, alcohol, and number of control. Analyses were only performed for significant results from
the first adjusted analysis.
Gabrhelík/Skurtveit/Nechanská/Mravčík/
Handal
Eur Addict Res 2023;29:19–29
26
DOI: 10.1159/000527238
the opioid group compared to the GP, increased risk of
certain infectious and parasitic diseases (aOR = 1.9; 1.3–
2.8) and certain conditions originating in the prenatal pe-
riod (aOR = 1.8; 1.7–4.5) was observed (Table3). There
was no increased risk for injury, poisoning, or diseases of
the ear when comparing the opioid group to the GP.
Stratified analysis on maternal hospitalizations related
to SUDs during the first 3 years after birth showed ten-
dency of higher ORs in all diagnostic categories com-
pared to children of women without such hospitalizations
(Table4). The most pronounced difference was observed
for the injury, poisoning, and certain other consequences
of external causes in the strata of the MA group who had
hospitalized mothers (aOR 6.3, 1.6–24.6) compared to
the strata without maternal hospitalizations (aOR 1.4,
0.9–2.3). Results from the stratified analyses on prema-
ture birth and small for gestational age are presented in
the online supplementary Table (for all online suppl.
material, see www.karger.com/doi/10.1159/000527238).
Stratified analyses showed mostly results in the same di-
rection in both strata as in the main analysis.
Discussion
We did not observe significant differences in morbid-
ity in the children of women using MA during pregnancy
compared to children of opioid using women during
pregnancy, as measured by the hospitalization measures
or the prevalence of ICD-10 diagnoses. By the age of three
years, children in both the MA and the opioid group had
higher risk of any hospitalization stay compared to the
GP, though the risk did not remain significant for the MA
group after adjustment. Other hospitalization measures
such as the total number of hospitalizations and length of
stay might still indicate more severe health conditions in
the children in the MA and opioid groups compared to
the GP. Children in the MA group received more diagno-
ses in several diagnostic chapters compared to the GP, but
after adjustment, the increased risk remained significant
only for the following diagnostic chapters: infectious and
parasitic diseases; diseases of the ear and mastoid process;
certain conditions originating in the prenatal period; and
injury, poisoning, and certain other consequences of ex-
ternal causes. Adjustment for the socio-economic factors,
illicit drug use, and the number of medical controls had a
profound effect in all the comparisons with the GP.
To our knowledge, there is a lack of studies on MA ex-
posure and morbidity in children beyond the perinatal
period. There is also a paucity of data regarding other
stimulants such as amphetamine, cocaine, and prescrip-
tion of stimulant drug use [24].
The most pronounced differences observed were be-
tween the two drug-exposed groups and the GP. MA and
opioids have different mechanisms of action, and both
have undesirable outcomes for the child. One part of the
explanation for these undesirable outcomes might be that
the adverse effects can be linked to the drug using lifestyle
common among both groups of pregnant women. This
might be supported by the quite strong effect of adjust-
ment for background characteristics and the number of
controls during pregnancy seen in the analyses. The effect
of socio-economic adjustment has been observed in stud-
ies of the association between several drugs and neonatal
outcomes previously [16, 17]. In the stratified analyses in
both the MA and opioid groups, we observed a tendency
of higher risk estimates in the group where the mother
was hospitalized for drug use drugs after birth. This sim-
ilar result for the two drugs might also support the impor-
tance of lifestyle associated with drug use.
Irrespective of the reason for increased childhood
morbidity, this study clearly showed that children in the
two drug-exposed groups had markedly higher risk of
hospitalization and on average two times longer hospital-
ization stays than children in the GP. For many diagnos-
tic chapters studied, the proportion of children was high-
er in both drug-exposed groups than in the GP. This in-
crease in morbidity is an important finding as it indicates
that these children would benefit from close health care
follow-up during childhood.
In a previous study, we showed that when MA- and
opioid-exposed newborns were compared, some neona-
tal outcomes were more favourable in the MA-exposed
[17]. In this study, no significant differences in childhood
morbidity between MA- and opioid-exposed children
were found. Nevertheless, all the hospitalization mea-
sures tended to be more favourable in the MA-exposed
children when compared to the opioid-exposed. The
same was observed for most diagnostic chapters.
When we compare the MA group with the GP, child
injuries were diagnosed more frequently in the MA-ex-
posed group. This was shown in both strata of maternal
substance-related hospitalizations, but we observed high-
er risk in the strata where the mother was hospitalized
after birth. This may refer to the negative role of the cha-
otic lifestyle of mothers and insufficient childcare that
may subsequently lead to an increased risk of injuries,
especially in women who use MA. This finding further
supports our previous findings that increased peri- and
postnatal morbidity of children could be linked to the life-
Morbidity in Methamphetamine-Exposed
Children
27
Eur Addict Res 2023;29:19–29
DOI: 10.1159/000527238
style and socio-economic situation of their mothers [14,
17].
The higher risk of congenital malformations in chil-
dren in the opioid group found in our study highlights the
potential teratogenicity of opioids. According to a recent
systematic review [25], positive associations were found
between congenital malformations and maternal opioid
use during pregnancy in more than half of the studies in-
cluded. Nevertheless, most of the included studies had
poor control over possible confounders including other
teratogenic substance use during pregnancy (such as al-
cohol), which might also explain part of the teratogenic
effect seen in our results.
Methodological Considerations
We created a national cohort using longitudinal data
from national registries of reproductive health, hospital-
ization, and death. Selection bias is therefore diminished
relative to many other clinical samples. Such national reg-
istries generate larger samples than those that may practi-
cally be used in clinical studies. Furthermore, recall bias
is also reduced with the inclusion of registry data.
For nearly a half century, MA has remained the most
commonly used illicit substance in Czechia [26] with a
high proportion of intravenous MA users [19], while the
use of other types of stimulants, such as amphetamine or
cocaine, is of very low prevalence [27]. This makes it pos-
sible to use the ICD-10 diagnosis F15 (stimulants use) to
identify MA users.
One limitation is our definition of women using MA
and opioids during pregnancy. We may not have identi-
fied a cohort of all pregnant women who have used sub-
stances while pregnant, rather only those whose use re-
sulted in hospitalization. We defined exposure as a diag-
nosis of SUD during pregnancy; yet, we may have
identified only the most problematic users. This defini-
tion could result in some misclassification. However, in
the case of an exposure with low prevalence, specificity
has a greater effect on the underestimation of risk than
does sensitivity [28]. By using our definition of MA use,
we have minimized the number of truly unexposed pa-
tients in the exposed group. An additional limitation re-
sults from the registers reporting MA as the primary
problematic drug, while other illicit drugs may have been
used in combination with MA. We also lack information
about timing, duration, or dose. We had no information
on burden of disease in the father or in the mother prior
and during pregnancy. Therefore, we did not have the
possibility to adjust for this information in our analysis.
Further, the results from the regression analysis only
show associations and do not point to causal effects, and
the results must be interpreted with caution.
According to general practice in the Czech Republic,
it seems that it is more common to hospitalize children in
the Czech Republic than in other western countries. Hos-
pitalizations due to childbirth were not included. In gen-
eral, when a patient/child is moved from one ward to an-
other for different health conditions (new diagnosis) dur-
ing one hospital stay, this is recorded as two separate
hospitalizations in the Czech registers. This may contrib-
ute to higher number of hospital stays. Finally, results of
the stratified analysis were affected by a low number in
different strata.
Conclusion
In this nation-wide cohort of children prenatally ex-
posed to MA, the total morbidity rate during the first 3
years of life was not significantly different from morbid-
ity in children prenatally exposed to opioids. Compared
to children in the GP, it seems like MA-exposed children
had higher risk of infections and injury, which may be as-
sociated with lower level of care due to socio-economic
conditions and the potentially chaotic lifestyle of moth-
ers. These findings need to be replicated in other coun-
tries, preferably in larger study samples.
Statement of Ethics
The study protocol has been approved by the Ethics Committee
of the General University Hospital, Prague, No. 89/14 Grant VES
2015 AZV 1. LFUK. Written informed consent from participants
was not required as this study used third-party data derived from
the state government registries and databases.
Conflict of Interest Statement
Roman Gabrhelík is the shareholder of Adiquit Ltd., which is
currently developing apps for addictions recovery. Nevertheless,
no funding was related to this study, and the activities had no role
in the study design or the data collection, analysis and interpreta-
tion of the data, writing the manuscript, or the decision to submit
the paper for publication. The remaining authors have no conflicts
of interest to declare.
Gabrhelík/Skurtveit/Nechanská/Mravčík/
Handal
Eur Addict Res 2023;29:19–29
28
DOI: 10.1159/000527238
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Funding Sources
The study was supported by the Ministry of Health of the Czech
Republic, Grant No. 16-28157A; Charles University Institutional
support ID: COP-Addictology; and the Norwegian Research
Council, Grant No. 240197/H10.
Author Contributions
Concept and design: Roman Gabrhelík, Svetlana Skurtveit,
and Marte Handal. Acquisition, analysis, or interpretation of
data: Svetlana Skurtveit, Blanka Nechanská, Roman Gabrhelík,
and Marte Handal. Blanka Nechanská had full access to all the
data in the study and takes responsibility for the integrity of the
data and the accuracy of the data analysis. Drafting of the man-
uscript: Roman Gabrhelík and Svetlana Skurtveit. Critical revi-
sion of the manuscript for important intellectual content: Ro-
man Gabrhelík, Svetlana Skurtveit, Marte Handal, and Viktor
Mravčík. Statistical analysis: Blanka Nechanská and Svetlana
Skurtveit. Obtained funding: Roman Gabrhelík, Blanka
Nechanská, Viktor Mravčík, Svetlana Skurtveit, and Marte
Handal. Administrative, technical, or material support: Ro-
man Gabrhelík. Supervision: Viktor Mravčík and Marte
Handal.
Data Availability Statement
This project uses third-party data derived from the state
government registries and databases, which are ultimately gov-
erned by their Ethics Committees and data custodians. Thus,
any requests to share these data will be subject to formal ap-
proval from each data source used in this project. Requests for
data sharing/case pooling may be directed to the correspond-
ing author’s email: roman.gabrhelik@lf1.cuni.cz. Requests for
code may be directed to Dr. Nechanská on email: nechanb@
seznam.cz.
Morbidity in Methamphetamine-Exposed
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