Health Risk Assessment of Toxic Metals Consumed Through Plant-Based Anti-Diabetic Therapeutics Collected in the Northern Divisional City of Rajshahi, Bangladesh

Abstract

The present study investigates human health risks upon consumption of herbal medicines in terms of ten toxic metals in twenty plant-based anti-diabetic therapeutics. The analysis of metals was determined by an atomic absorption spectrometer after microwave-assisted digestion. The computation of hazard quotients (HQ) and hazard indexes (HI) of metals leads to the assessment of non-carcinogenic health risks. Carcinogenic risk was assessed based on cancer slope factor (CSF) and chronic daily intake (CDI) values. Comparison with WHO regulatory cut-off points for each metal: seven samples for Mn, twelve samples for Hg, three samples for Cu, eight samples for Ni, four samples for Cd, two samples for Pb, one sample for Cr, and eight samples for Zn are unsafe to consume. Non-carcinogenic human health risk is predicted for Mn in seven samples, Fe in one sample, Hg in ten samples, Cu in three samples, Ni in one sample, and Pb in two samples. HI values greater than 1 predict non-carcinogenic health risk in thirteen samples. Incremental lifetime cancer risk (ILCR) remains for Pb in one sample, Cr in one sample, Cd in three samples, and Ni in nine samples. To guarantee consumer safety, the implementation of strict monitoring is suggested.

Full text

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Health Risk Assessment of Toxic Metals Consumed Through
Plant-Based Anti-Diabetic Therapeutics Collected in the
Northern Divisional City of Rajshahi, Bangladesh
Nazmul Islam
Daffodil International University
Rausan Zamir
University of Rajshahi
Omar Faruque
Jashore University of Science and Technology
Research Article
Keywords: Plant-based anti-diabetic therapeutics, carcinogenic and non-carcinogenic risks, hazard quotient, hazard index,
incremental lifetime cancer risk
Posted Date: May 31st, 2024
DOI: https://doi.org/10.21203/rs.3.rs-4442912/v1
License:   This work is licensed under a Creative Commons Attribution 4.0 International License.  Read Full License
Additional Declarations: No competing interests reported.

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Abstract
The present study investigates human health risks upon consumption of herbal medicines in terms of ten toxic metals in
twenty plant-based anti-diabetic therapeutics. The analysis of metals was determined by an atomic absorption
spectrometer after microwave-assisted digestion. The computation of hazard quotients (HQ) and hazard indexes (HI) of
metals leads to the assessment of non-carcinogenic health risks. Carcinogenic risk was assessed based on cancer slope
factor (CSF) and chronic daily intake (CDI) values. Comparison with WHO regulatory cut-off points for each metal: seven
samples for Mn, twelve samples for Hg, three samples for Cu, eight samples for Ni, four samples for Cd, two samples for
Pb, one sample for Cr, and eight samples for Zn are unsafe to consume. Non-carcinogenic human health risk is predicted
for Mn in seven samples, Fe in one sample, Hg in ten samples, Cu in three samples, Ni in one sample, and Pb in two
samples. HI values greater than 1 predict non-carcinogenic health risk in thirteen samples. Incremental lifetime cancer
risk (ILCR) remains for Pb in one sample, Cr in one sample, Cd in three samples, and Ni in nine samples. To guarantee
consumer safety, the implementation of strict monitoring is suggested.
1. Introduction
Plant-based therapeutics are essentially prepared from different medicinal herbs. Therapeutics are prone to
contamination with metals due to their source and nature. Herbs can be contaminated with metals during growing,
harvesting, and processing. Metals are considered persistent pollutants due to their non-biodegradability in nature [1, 2].
Different natural and anthropogenic activities render them available in nature. Continuous urbanization and
industrialization in the developing world have led to high levels of metal contamination in the soil and surrounding
environment [3, 4]. Entry routes for toxic metals in herbs in different stages are believed to be the following: polluted soils,
industrial emissions, transportation, water used in irrigation, fertilizers and pesticides, and storage processes [5–7]. The
manufacturing of herbs into nished formulations also contributes to metal contamination [8].
Plant-based therapeutics are conventionally used for the treatment and prevention of different chronic and acute diseases
like diabetes, hypertension, stomach pain, headaches, etc [5, 9]. With an increasing aging population and a change in
lifestyle, chronic diseases like diabetes are on rise. For the prevention and management of the disease, along with
allopathic drugs, plant-based anti-diabetic therapeutics are frequently used health resource [10, 11]. However, there has
been an increasing concern over the safety of these formulations due to their toxicity.
Affordability and availability fuel the popularity of plant-based therapeutics, where the claimed safe and harmless
advertisement of the medicines due to their natural origin plays a vital role [12]. However, the safety claim is made without
proper scientic evaluation. Studies conducted earlier in different countries revealed that herbal preparations contain
heavy metals beyond the World Health Organization’s (WHO) maximum permissible limit. The studies included but were
not limited to the following lead investigators: Haris and Yang in China [13, 14], Jurowski in Poland [15, 16], Bas gel in
Turkey [17], Saper in the United States of America [18], Garvey [19] etc. This may place drug safety at risk and affect public
health negatively.
Although some metals (Zn, Cu, Mn, Fe, etc.) are essential elements due to their role in biological systems, they become
harmful at high concentrations [2]. However, other metals (Hg, Pb, As, Cr, Cd, etc) are nonessential elements due to their
toxicity and are lethal even at very low concentration [20]. The chemical reactivity of the metal ions with cellular structural
proteins, enzymes, and membrane systems leaves them exposed to metal toxicity [8]. As a result, the threat of multi-
organ damage to consumers remains [21]. The damage leads to the onset of different diseases like decreased
immunological defenses, fetal malformation, cardiac dysfunction, gastrointestinal cancer, and impaired psychosocial and
neurological behavior [22, 23]. The safety and quality of plant-based therapeutics have become major concerns for
different stakeholders, which encompass general people, regulatory authorities, and pharmaceutical industries. However,
studies conducted into toxic metals in the formulations manufactured and sold in Bangladesh are scarce, and reported

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studies were under our research endeavors [12], which were based on samples collected from Dhaka City and its
surroundings.
Rajshahi forms an urban cluster of about ten lakh people, adding up two nearby satellite towns, Nowhata and Katakhali,
making it the fourth populous city of Bangladesh after Dhaka, Chottogram, and Khulna. Plant-based anti-diabetic
therapeutics are becoming widely used among city dwellers, among other herbal medicines. However, speculation
remains behind the regulation and monitoring of the safety of the products by the authorities concerned. Plus, no
information exists on the safety of plant-based therapeutics available from different outlets. As a result of the doubt, drug
safety may be in peril for the people living in the region. Therefore, the prediction of health risks for metals consumed
through therapeutics on a daily basis through non-carcinogenic and carcinogenic health risk assessment modeling has
been taken as the study objective.
2. Materials and Methods
2.1 Sample
The Rajshahi City Corporation area was chosen for sample collection. Sampling was done from different herbal drug-
selling outlets of different manufacturers. Several plant-based anti-diabetic therapeutics were provided by each
manufacturer. Only samples available as nished commercial packs were purchased. Purchased samples were found
with their drug administration registration number (DAR No.). Plant-based therapeutics selling outlets show similar
characteristics, like that the areas where the outlets were housed were densely populated, where people purchase drugs
from the close vicinity of their residing location, and the formulations selling outlets were situated in places where there is
mass transferring of people, making the areas junctions for people. As a result, when people were heading to the city for
their works, on the way the outlets appeared, and they ended up buying their necessary drugs.
Purchased samples were preserved as per the preservation instructions written on the packaging wall or supplied patient
information leaets (PILs). Sample blindfolding was performed prior to analysis by means of their identity masking by
codes (Table 1).


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Table 1
The brief information of the investigated plant-based anti-diabetic therapeutics
Sample code Batch No. Dosage Unit Drug Weight. gm DAR No.
S 1 54 2 Table 2 times daily 0.41 U-038-A-029
S 2 81 2 Table 2 times daily 0.40 U-038-A-028
S 3 1 2 Table 3 times daily 0.57 U-038-A-017
S 4 4 2 Table 2 times daily 0.57 U-038-A-021
S 5 8 2 Table 1 times daily 0.57 U-038-A-018
S 6 1 4 cap 3 times daily 0.54 U-038-A-100
S 7 1 1 Table 2 times daily 0.96 U-038-A-074
S 8 6 2 Table 2 times daily 0.64 H-82-A-61
S 9 5 10 gm powder 3 times daily 0.62 N/A
S 10 5 5 Table 3 times daily 0.59 H-82A-054
S 11 8 2 Table 2 times daily 0.66 H-47A-061
S 12 6 2 Table 3 times daily 0.65 003-02-94
S 13 5 2 Table 3 times daily 0.64 U19-A-128
S 14 9 2 Table 2 times daily 0.63 U-19-A-040
S 15 5 1 cap 2 times daily 0.64 U-19-A-219
S 16 9 1 cap 2 times daily 0.60 015-0005-94
S 17 15 1 sachete 3 times daily 3.82 Ayu-78A-019
S 18 1 2 cap 2 times daily 0.60 015-14-94
S 19 2019-06/1(2) 3 tab two times daily 0.25 Ayu-A-310
S 20 2019-06/1(1) 3 tab two times daily 0.50 Ayu-A-309
2.2 Sample drying
Inside the laboratory, coded samples were opened from plastic packaging. Samples were placed in individual porcelain
dishes and placed in the oven. The oven temperature was programmed at 700C to reach a constant weight of samples.
Oven-dried samples were converted to ne powder by pulverization using a mortar pestle, which were preserved in plastic
vials inside the desiccator to cancel any possibility of moisture gain.
2.3 Sample digestion
Homogeneous powder (1 g) was taken in Teon vessel, and 10 mL of conc. HNO3 acid (Merck, Germany) was added to
the samples, followed by 2 mL of 30% H2O2 (Sigma-Aldrich) addition. The mixture was placed in a microwave digestion
chamber (Milestone-Ethos One, USA). Temperature (1800C) was applied for 15 minutes to complete digestion, which
decomposes organic materials from the sample matrix, leaving metals in solution. The mass was ltered (Whatman lter
paper) and quantitatively transferred to a 25- mL volumetric ask [5].

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2.4 Sample analysis
Metal quantication was done by an atomic absorption spectrophotometer (AA-7000, Shimadzu, Japan) [12]. The
spectrophotometer was operated in different modes: ame atomizer (FA), cold vapor (CV), and graphite tube atomizer
(GTA), depending on the necessity. Cadmium, chromium, copper, iron, manganese, nickel, lead,; and zinc were atomized
by ame atomization, arsenic was atomized by a graphite tube atomizer; and mercury was atomized by a cold vapor
atomizer. An air-acetylene oxidizing ame was used as a ame gas. Standard stock solutions of 1000 mg/L (Wako
Chemicals, Japan) of each metal were diluted to working standards for calibration. Samples were diluted and fed to
autosampler, followed by atomization. The spectrophotometer was provided with single-element hollow cathode lamps
and a 10-cm air acetylene burner. According to the requirements of the manufacturer, the spectral band pass, the
wavelengths, and other instrumental conditions were set (Table 2).

Table 2
Instrumental Operating Conditions
Metal Sample ow rate,
mL/ min
Lamp Wave length,
nm
Slit width, nm Lamp intensity, mA
Mn 5 HCL 193.70 1.00 7
Fe 5 HCL 228.80 0.50 3
Hg 5 HCL 357.90 0.20 7
Cu 5 HCL 324.70 0.50 3
Ni 5 HCL 372.00 0.20 7
Cd 5 HCL 217.00 1.00 5
Pb 5 HCL 279.50 0.20 5
Cr 5 HCL 240.70 0.20 7
As 5 HCL 232.00 0.20 7
Zn 5 HCL 232.00 0.50 5
HCL = hollow cathode lamp
2.5 Quality control
The data was validated by goodness of tness studies and recovery studies (standard recovery and spike). Calibration
curves were constructed by plotting absorbance against concentration. The coecient of determination (R2) values was
obtained from calibration curves for each metal and judged for goodness of tness. Coecient of determination (R2)
values was obtained in the range of 0.9992–0.9999 for the metals under investigation. Prepared standards were re-run
under the same calibration as the samples. The minimum recovery was 93% for manganese, and maximum recovery was
111% for mercury. Into the standard of each metal, the known amount of the respective addition was done to see the
spike recovery. The minimum recovery was 79% for iron, and the maximum recovery was 129% for cadmium (Table 3).


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Table 3
Quality control
Metal Goodness of tness study Recovery study
Regression equation Coecient of determination Standard
recovery %,
n = 5
Spike
recovery %, n = 3
Mn y = 0.2315 x + 0.0039 0.9991 93–105 90–97
Fe y = 0.1085x + 0.0012 0.9997 96–104 79–91
Hg y = 0.015 x − 0.0012 0.9994 105–111 98–115
Cu y = 0.1383x + 0.0007 0.9999 97–109 84–111
Ni y = 0.1146 x -0.0008 0.9994 96–100 96
Cd y = 0.5347 x − 0.0034 0.9999 101–104 103–129
Pb y = 0.0236 x + 0.0002 0.9997 98–101 93–118
Cr y = 0.1141 x + 0.0044 0.9982 104–110 89–119
As y = 0.0125 x − 0.0037 0.9987 96–103 83–106
Zn y = 0.5275 x + 0.0026 0.9990 95–103 118
Furthermore, the accuracy and precision of the instrumental analysis were checked by testing repeatedly the certied
reference materials SRM 1571 (trace elements in Orchard leaves, National Bureau of Standards Certicate of Analysis,
USA). Mn, Cu, Pb and Zn were recovered 96.7%, 112.5%, 102.2%, and 93.6% respectively.
2.6The health risk assessment of toxic metals intake through plant-
based anti-diabetic therapeutics
Over a period of time prolonged exposure to an individual metal can result in harmful health impacts. Risk assessment is
the method for evaluating the probability of the occurrence of such health impacts. The health risk assessment models
depend on the estimation of risk level. Two types of modeling are available: non-carcinogenic health risk assessment and
carcinogenic health risk assessment. Non-carcinogenic health risk was evaluated by determining estimated daily
exposure (EDI), chronic daily intake (CDI), hazard quotient (HQ) and hazard index (HI) [2, 24]. Carcinogenic risk was
assessed from the cancer slope factors of metals in interest (Table 4).


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Table 4
Parameters and input assumptions for health risk
assessment of metal through samples
Parameter Unit Values
Metal concentration mg/kg -
Estimated daily intake (EDI) mg/ kg/ day -
Chronic daily intake (CDI) mg/ kg/ day -
Exposure Frequency(EF) Days/ year 365
Exposure duration (ED) Years 20
Body weight (BW) Kg 65
Average time (AT) ED× 365 days 7300
2.6.1The estimated daily intake of toxic metals based on the oral
intake of plant-based anti-diabetic therapeutics
Estimated daily intake (EDI) is the daily consumption of toxic metals. The EDI value is computed by multiplying the
concentration of metal in the sample with ingestion rate and by dividing the result by the human body weight [25]. The
formula for calculating EDI is:
Where
-C (mg/ kg) is the concentration of toxic metals in the plant-based anti-diabetic therapeutics.
-IR (kg/ day) is the ingestion rate and
-BW (kg) is the human body weight.
2.6.2The chronic daily intake of toxic metals based on chronic exposure of toxic metals through plant-based anti-diabetic
therapeutics
Chronic daily intake (CDI) is the daily consumption of toxic metals for a long time. As most of the herbal drugs are
consumed orally, the chronic intake computation is based on oral exposure. The formula for calculating CDI is:
Where
-CDI (mg/kg/day) is the chronic daily intake
-EF (days/ year) is the exposure frequency
-ED (years) is the exposure duration and
-AT (ED ) (days) is the averaging time [26].
EDI
= (1)
C
×
IR
BW
CDI
= (2)
EDI
×
EF
×
ED
AT
×365

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2.6.3 Health risk assessment of individual toxic metals through
intake of plant-based anti-diabetic therapeutics
Hazard quotient (HQ) is the ratio of chronic daily intake (CDI) to reference dose (RfD) of the metal in interest [27]. The
formula for calculating the hazard quotient is:
Where
-RfD is the reference dose that enable individual to sustain the level of exposure over a long period of time without
experiencing any harmful effects [28] (Table 5).
If HQ < 1, there concern for non-carcinogenic health risk doesn’t exist and if HQ , there is reason for non-carcinogenic
anxiety[29].

Table 5
Reference dose [27, 28] and cancer slope factors of
different metals
Metal Oral RfD1
(mg/Kg/Day)
CSF2
(Kg/day/mg)
Mn 0.14 -
Fe 0.70 -
Hg 0.0001 -
Cu 0.001 0.84
Ni 0.02 6.10
Cd 0.001 8.50
Pb 0.004 41.00
Cr 0.02 
As 0.003 
Zn 0.30 
1RfD= reference dose, 2CSF= cancer slope factor
2.6.4The total health risk of multiple toxic metals through intake of
plant-based anti-diabetic therapeutics
The hazard index (HI) aids in evaluating the overall non-carcinogenic risk to human health when more than one toxic
metal is being consumed through a sample drug. It is believed that exposure to more than one metal can cause additive
effects. The hazard index (HI) was computed as the sum of all hazard index values for metal [30]. The formula for
calculating the hazard index is:
HQ
= (3)
CDI
RfD
> 1

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HI value greater than 1 indicates a possibility of adverse effects on human health[30].
2.6.5 Incremental lifetime cancer risk of individual carcinogenic
metals through intake of plant-based anti-diabetic therapeutics
The probable cancer risks due to exposure to a specied dose of toxic metal in herbal drugs can be estimated using the
Incremental Lifetime Cancer Risk (ILCR). The ILCR indicates the incremental probability of a person developing any type
of cancer over exposure duration as a result of daily exposure to a given daily amount of a carcinogenic element for
years. The estimation is a product of chronic daily intake (CDI) and cancer slope factor (CSF) [29].
Where
-CSF is the risk generated by a lifetime average amount of one mg/kg/day of carcinogen metal.
The permissible limit for ILCR are considered to be 10− 4 for a single carcinogenic element [31].
3. Results
3.1 Daily intake of individual toxic metal through plant-based anti-
diabetic therapeutics
The minimum, mean, and maximum levels of EDI and CDI are provided (Table6). The mean EDI followed the following
trend: Mn > Fe > Cr > Pb > Hg > Ni > Zn > Cu > As > Cd. The mean CDI abides by the following trend: Mn > Fe > Pb > Hg > Zn >
Ni > Cu > Cr > As > Cd.
Table 6
Daily intake of metals through samples
Metal 1EDI, mg/ kg bw/ day 2CDI, mg/ kg bw/ day
Mean Max Min Mean Max Min
Mn 8.15E-01 5.51E + 00 1.80E-04 8.15E-01 5.51E + 00 1.80E-04
Fe 7.42E-02 7.84E-01 1.65E-03 7.42E-02 7.84E-01 1.65E-03
Hg 1.45E-02 1.83E-01 7.16E-06 1.45E-02 1.83E-01 7.16E-06
Cu 1.58E-03 4.13E-03 4.62E-07 1.58E-03 4.13E-03 4.62E-07
Ni 7.58E-03 3.73E-02 3.54E-05 7.58E-03 3.73E-02 3.54E-05
Cd 3.77E-05 0.00E + 00 1.15E-06 3.77E-05 9.54E-05 1.15E-06
Pb 3.02E-02 3.48E-01 2.22E-05 3.02E-02 3.48E-01 2.22E-05
Cr 3.02E-02 3.48E-01 2.22E-05 7.63E-04 7.63E-04 7.63E-04
As 7.26E-05 2.80E-04 1.05E-05 7.26E-05 2.80E-04 1.05E-05
Zn 7.01E-03 4.22E-02 1.44E-04 7.01E-03 4.22E-02 1.44E-04
HI
=
n
∑
1
HQi
(4)
ILCR
=
CDI
×
CSF
(5)

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1EDI= Estimated daily intake, 2CDI= Chronic daily intake.
3.2 Health risk of individual toxic metal and multiple toxic metals through intake of plant-based anti-diabetic therapeutics
The mean HQ followed the following pattern: Hg > Pb > Mn > Cu > Ni > Fe > Cd > Cr > Zn > As (Table7).
Table 7
Hazard quotient and hazard index values of meats in each sample
Sample
Code
1HQ 2HI
Mn Fe Hg Cu Ni Cd Pb Cr As Zn
S 1 . 0.00 0.29 . . . . . . 0.00 0.30
S 2 . 0.11 0.17 . . . 0.03 . 0.01 0.01 0.33
S 3 0.01 0.01 0.10 . . . . . 0.00 0.00 0.12
S 4 0.01 0.02 0.26 . . . . . . 0.00 0.28
S 5 0.00 0.01 0.07 . . . . . . 0.00 0.08
S 6 0.05 0.06 0.84 4.13 . . . . . 0.05 5.12
S 7 0.01 0.01 0.11 2.15 0.20 . . . . 0.00 2.47
S 8 5.34 0.02 0.35 . 0.22 . 0.02 . . 0.01 5.95
S 9 39.32 0.08 5.76 . 1.86 . 0.10 . . 0.04 47.18
S 10 28.23 0.09 3.26 3.06 0.80 0.03 0.03 . . 0.12 35.62
S 11 5.74 0.01 1.16 . 0.30 . 0.01 . . 0.00 7.22
S 12 8.85 0.10 1.56 . 0.27 . 0.01 . . 0.01 10.80
S 13 0.03 0.02 11.79 0.14 0.00 . 0.06 . 0.00 0.01 12.05
S 14 0.01 0.04 0.85 . . . . . . 0.00 0.90
S 15 0.00 0.01 7.40 . 0.00 . . . . 0.00 7.41
S 16 0.00 0.00 11.46 . . . 0.02 . . 0.00 11.49
S 17 0.10 1.12 66.21 . 0.03 . 3.31 0.04 0.01 0.14 70.95
S 18 0.01 . . . . 0.10 0.05 . 0.09 . 0.25
S 19 4.32 0.02 817.62 0.00 0.18 0.00 0.01 . . 0.01 822.16
S 20 12.73 0.30 1829.96 0.00 0.29 0.03 86.88 . 0.02 0.03 1930.24
Mean 5.82 0.11 145.22 1.58 0.38 0.04 7.54 0.04 0.02 0.02 
Max 39.32 1.12 1829.96 4.13 1.86 0.10 86.88 0.04 0.09 0.14 
Min 1.29E-
03 2.35E-
03 7.16E-
02 4.62E-
04 1.77E-
03 1.15E-
03 5.54E-
03 3.81E-
02 3.49E-
03 4.81E-
04 
1HQ= Hazard quotient, 2Hazard index
HI values crossed cut-off value(HI
> 1)in13samples.

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3.3 Health risk of carcinogenic metals through intake of plant-based
anti-diabetic therapeutics
The mean values for incremental lifetime cancer risk (ILCR) follows the following trend: Pb > Ni > Cr > Cd.
Table 8
Incremental Lifetime Cancer Risk
Sample
Code
1ILCR
Pb Cr Cd Ni
S 1 0.00E + 00 0.00E + 00 0.00E + 00 0.00E + 00
S 2 9.93E-04 0.00E + 00 0.00E + 00 0.00E + 00
S 3 0.00E + 00 0.00E + 00 0.00E + 00 0.00E + 00
S 4 0.00E + 00 0.00E + 00 0.00E + 00 0.00E + 00
S 5 0.00E + 00 0.00E + 00 0.00E + 00 0.00E + 00
S 6 0.00E + 00 0.00E + 00 0.00E + 00 0.00E + 00
S 7 0.00E + 00 0.00E + 00 0.00E + 00 3.33E-03
S 8 5.84E-04 0.00E + 00 0.00E + 00 3.76E-03
S 9 3.44E-03 0.00E + 00 0.00E + 00 3.13E-02
S 10 9.54E-04 0.00E + 00 1.73E-04 1.35E-02
S 11 4.31E-04 0.00E + 00 0.00E + 00 5.04E-03
S 12 1.88E-04 0.00E + 00 0.00E + 00 4.58E-03
S 13 1.98E-03 0.00E + 00 0.00E + 00 7.30E-05
S 14 0.00E + 00 0.00E + 00 0.00E + 00 0.00E + 00
S 15 0.00E + 00 0.00E + 00 0.00E + 00 2.98E-05
S 16 7.09E-04 0.00E + 00 0.00E + 00 0.00E + 00
S 17 1.12E-01 3.13E-02 0.00E + 00 4.73E-04
S 18 1.74E-03 0.00E + 00 5.82E-04 0.00E + 00
S 19 2.04E-04 0.00E + 00 7.04E-06 3.08E-03
S 20 2.95E + 00 0.00E + 00 1.58E-04 4.82E-03
Mean 1.54E-01 1.56E-03 4.60E-05 3.50E-03
1ICLR= incremental lifetime cancer risk
3.4 Toxic metal concentration quantied in different plant-based anti-diabetic therapeutics by their comparison with
international regulatory authority safety values
The mean, minimum, and maximum concentrations of metals found in the investigated samples were presented
(Table9). As metal contamination in plant-based therapeutics can increase the likelihood of health risks, the risks were
assessed by non-carcinogenic and carcinogenic risk assessment modeling. A wide variation in mean values of metal

Page 12/15
concentrations was observed. The mean metal concentration follows the following trend: Mn > Fe > Pb > Hg > Ni > Zn > Cu
> Cr > As > Cd (Table10).
Table 9
Description of toxic metal concentrations in different plant-based anti-diabetic
therapeutics and their comparison with international regulatory authority safety
values
Metal 1DS Mean Min Max 2WHO limits [11]3US
Mn 18 9609.32 10.30 38549.00 320.00 7
Fe 19 929.34 89.60 4467.00 NA N/A
Hg 19 403.93 0.19 3957.00 1.00 12
Cu 6 23.19 0.01 72.50 3.00 3
Ni 11 93.13 1.46 159.00 10.00 8
Cd 4 0.84 0.05 2.56 0.02 4
Pb 12 634.60 0.37 7515.00 10.00 2
Cr 1 4.32 4.32 4.32 0.05 1
As 6 1.87 0.11 7.50 10.00 0
Zn 19 75.57 7.86 263.80 50.00 8
1DS= Detected sample, 2WHO= World Health Organization, 3US= Unsafe sample
4. Discussion
Ten metals-Mn, Fe, Hg, Cu, Ni, Cd, Pb, Cr, As, and Zn- were searched for and quantied in twenty plant-based anti-diabetic
therapeutics. Metal concentrations were fed into health risk assessment modeling. A health risk assessment of toxic
metals is usually performed to estimate the total exposure of heavy metals among the residents. Risk assessment of
toxic metals in humans is based on a mechanistic assumption, which is that metals may either be carcinogenic or non-
carcinogenic. Non-carcinogenic assessment is based on determination of estimated daily intake (EDI), followed by
chronic daily intake (CDI), hazard quotient (HQ) and hazard index (HI).
The following samples were thought to pose serious health hazards for Mn for their hazard quotient value greater than 1:
S 8, S 9, S 10, S 11, S 12, S 19, and S 20. Only one drug, S-17 is likely to pose adverse health effects for Fe due to its
exceeding HQ value cut -off point. The presence of Hg can cause adverse health effects upon consumption of the
following samples: S 9, S 10, S 11, S 12, S 13, S 15, S 16, S 17, S 19, and S 20. With greater than 1 HQ for Cu, the following
samples are of concern: S 6, S 7, and S 10. Just one sample, S 9 (1.8636 mg/kg/day) was deemed risky for possible
adverse health hazards due to the presence of Ni in it, which showed an exceeding HQ value from the cut-off point. For
Cd, none of the investigated samples pose adverse health effect due to their below 1 hazard quotient value. The following
samples showed concerning hazard quotient for Pb: S 17 and S 20. All of the investigated samples don’t pose adverse
health effects for Cr due to their below 1 hazard quotient value. However, quite contrarily, none of the plant-based
therapeutics exceeded the cut-off value (HQ > 1) for Cr in African investigation [32]. For As and Zn, none of the probed
samples shouldn’t cause any adverse effect on human health due to the below 1 HQ values of all of the investigated
samples. The HI values of the following samples crossed cut-off value and put risk on human health upon consumption: S
6, S 7, S 8, S 9, S 10, S 11, S 12, S 13, S 15, S 16, S 17, S 19, and S 20. In disagreement with our investigation, a Brazilian
investigation didn’t nd a non-carcinogenic health risk in any samples for concurrent toxic metals (HI [33].
< 1)

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Carcinogenic assessment is based on the determination of incremental lifetime cancer risk (ILCR) from cancer slope
factor (CSF) and chronic daily intake (CDI). Among the investigated metals, Pb, Cr, Cd, and Ni are considered
carcinogenic. ILCR remains in one sample (S 20) for Pb. The possibility of ILCR exists in one sample (S 17) for Cr. For Cd,
concern remains in three samples (S 10, S 18, and S 20) due to their computed ILCR. The following samples, S 7–12, S 17,
S 19, and S 20, are of concern for Ni due to ILCR (Table8). Samples with cancer risks in varying degrees were seen for Pb,
Cr, and Ni in another investigation [34].
The highest and lowest mean metal concentrations were seen in Mn (9609.32 ppm) and Cd (0.84 ppm), respectively.
Metals were quantied in the following range: 10.30- 38549.00 mg/ kg for Mn, 89.60–4467.00 mg/kg for Fe, 0.19–
3957.00 mg/kg for Hg, 0.01–72.50 mg/kg for Cu, 1.46–159.00 mg/kg for Ni, 0.05–2.56 mg/kg for Cd, 0.37–7515.00 mg/
kg for Pb, 4.32–4.32 mg/kg for Cr, 0.11–7.50 mg/kg for As, and 7.86–263.80 mg/kg for Zn. For each metal, except Fe,
regulatory authority, WHO, sets its safety ceiling, above which concerns exist [12]. Unsafe samples follow the trend: Hg >
Ni > Zn > Mn > Cd > Cu > Pb > Cr > As. Metals exceeding safety limits in samples in varying degrees were documented in
Asian [13, 14, 17], European [15, 16], and American [18] investigations. Metal ions cause toxicity by interacting with
cellular structural proteins, enzymes, and membrane systems [35], thereby generating a threat to multi-organ damage to
patients [21].
Metal deposition in raw herbal plants can result from ambient pollution and soil composition where plants are grown,
which can expose people to harmful metals in herbal medicines. Furthermore, if appropriate production and laboratory
procedures are not followed, many phases of the manufacturing process also serve as entrance points for metal
contamination in herbal treatments.
5. Conclusions
Through carcinogenic and non-carcinogenic risk assessment modeling, human health risk was assessed for ten metals
consumed through different plant-based anti-diabetic therapeutics. The mean metal concentration follows the following
trend: Mn > Fe > Pb > Hg > Ni > Zn > Cu > Cr > As > Cd. Metals were detected in the following range: Mn: 10.30- 38549.00
mg/kg, Fe: 89.60–4467.00 mg/kg, Hg: 0.19–3957.00 mg/kg, Cu: 0.01–72.50 mg/kg, Ni: 1.46–159.00 mg/kg, Cd: 0.05–
2.56 mg/kg, Pb: 0.37–7515.00 mg/kg, Cr: 4.32–4.32 mg/kg, As: 0.11–7.50 mg/kg and Zn: 7.86–263.80 mg/kg. According
to regulatory authority safe limits for each metal, the following number of samples were unsafe: Mn (35%), Hg (60%), Cu
(15%), Ni (40%), Cd (20%), Pb (10%), Cr (5%), and Zn (40%). None of the samples were found unsafe for As. The mean EDI
and mean CDI maintained the following pattern: Mn > Fe > Cr > Pb > Hg > Ni > Zn > Cu > As > Cd and Mn > Fe > Pb > Hg > Zn
> Ni > Cu > Cr > As > Cd, respectively. Mean HQ abided by the following pattern: Hg > Pb > Mn > Cu > Ni > Fe > Cd > Cr > Zn >
As. Non-carcinogenic human health risk is predicted in 35% samples for Mn, 5% samples for Fe, 50% samples for Hg, 15%
samples for Cu, one sample, 5% samples for Ni, 10% samples for Pb, and no samples pose a health threat for Cd, Cr, As,
and Zn. The metals concurrently made 65% of the samples unsafe due to their non-carcinogenic health risk indications in
their HI values (greater than 1). The mean ILCR value follows the pattern Pb > Ni > Cr > Cd. ILCR remains in 5% samples for
Pb, 5% samples for Cr, 15% samples for Cd, and 45% samples for Ni. This probe noties the scientic community that
there would be both non-carcinogenic and carcinogenic health risks to the consumer associated with the consumption of
plant-based anti-diabetic therapeutics collected from Rajshahi City, Bangladesh. This would enable them to conduct more
assays into different market available plant-based therapeutics to learn the actual scenario.
Declarations
Author Contributions:Conceptualization, N.I. and R.Z.; methodology, N.I. and R.Z.; software, N.I.; validation, R.Z., N.I., and
O.F.; formal analysis, N.I.; investigation, N.I.; resources, R.Z.; data curation, N.I.; writing—original draft preparation, N.I.;
writing—review and editing, N.I. and R.Z.; visualization, N.I.; supervision, R.Z. and O.F.; project administration, N.I.; funding
acquisition, R.Z. All authors have read and agreed to the published version of the manuscript.

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Funding:This research was funded by International Science Program (ISP), Uppsala University, Sweden through SIDA,
grant number BAN-05, 2021-2024.
Data Availability Statement:Data is provided with the manuscript.
Conicts of Interest:The authors declare no conict of interest.
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