Health risks from multiroute exposure of potentially toxic elements in a coastal community: a probabilistic risk approach in Pangkep Regency, Indonesia

Abstract

Populations in coastal areas are vulnerable to chronic exposure to potentially toxic elements (PTEs) from aquatic ecosystems. In this study, we estimated the health risks from Cd, Cr, Fe, and Pb exposure in river water, sediments, and edible aquatic biota (Anadara granosa and Chanos chanos). Human daily intake was determined by an interview process with 287 respondents that were selected by proportional cluster random sampling. The cumulative probability value for total risk exceeded the acceptable limit value, indicating that adverse health impacts from PTE exposure may occur in the Pangkep coastal population. The sensitivity analysis showed that exposure duration and Cr concentrations are the factors with the greatest influence in a recreational exposure scenario, whereas the frequency of exposure to shellfish and milkfish is the most influential factor for health risks in a residential scenario. Thus, reducing Cr concentrations in river water, restricting swimming duration, and limiting the frequency of shellfish and milkfish consumption are required to mitigate health risks in the future.

Keywords:

• Carcinogenic risk
• noncarcinogenic risk
• probabilistic risk assessment
• river pollution
• toxic metals

Introduction

The presence of potentially toxic elements (PTEs) in aquatic ecosystems is harmful not only to aquatic organisms but also to terrestrial organisms, including humans. This problem remains an issue of major concern worldwide because of the toxicity of such elements and their ability to accumulate in biological tissues. Thus, the presence of PTEs poses a threat to food chains. Several PTEs such as As, Hg, Pb, and Cd can cause adverse health problems at very low concentrations (Rahman et al. 2012; Jaishankar et al. 2014; Azeh et al. 2019; Rovira and Domingo 2019). The most recent blood lead reference value (BLRV) proposed by the CDC (2012a) is far lower than the previous blood lead level value (10 µg/dL). Moreover, the new BLRV value for children is 3.5 µg/dL, indicating that special actions must be implemented for children who have BLRV at or above the reference value to prevent further exposure and health impacts (CDC 2012b). Pb, Cd, and Cr are considered to be the most toxic substances in the substance priority list produced by ATSDR (2019). Although Fe is considered to be an essential PTE because it plays a role in mitochondrial function and enzyme regulation, exposure to high Fe concentrations can cause protein deterioration and induce DNA alteration, thereby provoking cell death (González et al. 2017). Additionally, excess iron leads to the accumulation of reactive oxygen species, affects the transformation of genes that regulate hematopoiesis, and disrupts hematopoiesis in bone marrow (Isidori et al. 2018), which also causes hemochromatosis (disruption of five genes responsible for iron absorption, iron transportation, and an iron-sensing protein regulator) (Zhang et al. 2019).

Carcinogenic PTEs such as As, Cd, and Cr may disrupt DNA synthesis and repair mechanisms (Clancy et al. 2012; Koedrith et al. 2013). Additionally, Cd exposure is associated with bone and kidney damage, and Cd exposure can cause liver damage, gastrointestinal disorders, lung injuries, degenerative bone disease, prostatic proliferative lesion, hypertension, and bone fractures and can disrupt Zn and Cu metabolism (Satarug et al. 2010, 2018; Zeinali et al. 2019; Balali-Mood et al. 2021). Pb is a neurotoxic PTE that is associated with developmental and neurobehavioral effects, especially in fetuses and children (WHO 2007). Several studies have shown that Pb exposure promotes respiratory, urinary, hematological, neurological, neuropathy, and cardiovascular disorders through immune modulation, inflammatory, and oxidative mechanisms (Bernhoft 2012; Tsai et al. 2017; Balali-Mood et al. 2021; Das et al. 2021). Chronic exposure to Cr can induce various diseases such as dermal, renal, neurological, and gastrointestinal system disorders as well as cancers (lung, larynx, kidney, testicles, thyroid, and bladder) (Fang et al. 2014).

The Pangkajene river is located in the Pangkajene dan kepulauan (Pangkep) regency in South Sulawesi Province, Indonesia. It flows from the east to the west part of the city across the karst hills and ends in the Makassar strait. This river is used as a source of freshwater for many human activities such as irrigation, industrial and aquaculture/fish farming activities, navigation, and domestic activities. Its location near the site of various human activities that can potentially pollute the river ecosystem has caused the water quality of the Pangkajene river to decrease over recent years, which may also influence the nearby coastal areas that receive water containing run-off from the land. PTEs and other pollutants may be carried by river water to coastal areas, where they can disrupt normal aquatic activity, and most PTEs can cause serious threats to communities that use contaminated water for drinking, irrigation, and recreation purposes. Additionally, populations in coastal areas are more vulnerable to PTE exposure through dietary intake, especially from aquatic organisms such as shellfish, milkfish, fish, and shrimp, which are sources of nutritious food. Milkfish (Chanos chanos) and shellfish (Anadara granosa) are often consumed by Pangkep communities and are important sources of protein. Thus, the coastal community experiences greater potential exposure to PTEs through multiple environmental pathways, such as water and sediment while swimming, and/or the consumption of aquatic animals such as shellfish and milkfish taken from river water.

Human health risk assessments (HHRA) have been widely used by several researchers to assess potential adverse health effects that may occur in the future because of chronic exposure to trace elements from the aquatic environment (Yi et al. 2017; Ezugwu et al. 2019; Gao et al. 2019; Mgbenu and Egbueri 2019; Ukah et al. 2019; Egbueri 2020; Egbueri and Mgbenu 2020; Onyemesili et al. 2020; Astuti et al. 2021a; Enyigwe et al. 2021; Karmakar et al. 2021; Rauf et al. 2021b). Those previous studies revealed that many sources of PTE contamination exist in aquatic settings, such as mining; agricultural, domestic, and industrial activities; and geogenic sources. However, very little research has evaluated the health risks to coastal communities related to PTE contamination in the study area investigated here. Previous HHRA studies only assessed exposure to one particular metal (such as As or Cr) (Aripai et al. 2012; Bahar and Daud 2012). However, PTEs have the potential to cause health problems in the form of combined elements through exposure to multiple mediums and pathways. The complex health risks due to combinations of PTEs in coastal communities have not yet been assessed. Moreover, a prior study only estimated health risks using reference/standard values from the U.S. Environmental Protection Agency (USEPA) and other works of literature. They did not calculate risks on the basis of the real dietary intakes and exposure patterns of the local communities. Failure to address these factors can cause bias in health risk assessments. This is the first study that has calculated risks from a combination of PTEs and used the actual exposure patterns of the Pangkep community.

High uncertainties may be involved in conducting risk estimations. The uncertainty may originate from variation in environmental conditions, insufficient knowledge of the actual value of certain variables, and characteristics of the population (Sanaei et al. 2021). Previous studies of human health risks have not dealt with the uncertainty that may be present. Moreover, several studies use the standard value of human exposure patterns from USEPA to calculate risks, which may not be appropriate for the inhabitants of the study area. This can cause policy making designed to reduce health risks from environmental PTE exposure to be incompatible with the existing conditions in the region. Thus, a comprehensive estimation incorporating uncertainties associated with human health risk assessments is needed to more convincingly determine the possibility of further impacts from PTE exposure on human health.

Monte Carlo simulation (MCS) is a mathematical and logical model that has been widely used to assess uncertainty in health risk assessment models by collecting limited data to comprehensively predict various situations (Xiao et al. 2018; Sanaei et al. 2021). MCS can be applied to calculate uncertainties and conduct sensitivity analyses of random variables in human health risk assessments (Qu et al. 2012). This model was used by USEPA as the basis to consider health risk policy. Thus, to adequately consider the uncertainty that may be present, we used MCS to estimate health risks. The aims of this study are (1)(1) $${\mathrm{HQ}}_{\mathrm{ingestion}-w\mathrm{ }}=\frac{C_{rw}\mathrm{ }\times \mathrm{ }{\mathrm{IR}}_{\mathrm{rec}-w}\mathrm{ }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ED}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{EV}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ET}}_{\mathrm{rec}}}{\mathrm{BW}\mathrm{ }\times \text{ AT }\times \mathrm{ }{\mathrm{RfD}}_{\mathrm{o}}}$$(1) to evaluate potential noncarcinogenic and carcinogenic risks due to PTE exposure through multiple exposure pathways and (2)(2) $${\mathrm{HQ}}_{\mathrm{dermal}-w}=\frac{C_{rw}\mathrm{ }\times \text{ SA }\times \mathrm{ }{K}_p\mathrm{ }\times \mathrm{ }{\mathrm{ET}}_{\mathrm{rec}}\mathrm{ }\times \text{ EV }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ED}}_{\mathrm{rec}-w}\mathrm{ }\times \mathrm{ }{\mathrm{CF}}_w}{\mathrm{BW}\mathrm{ }\times \text{ AT }\times \mathrm{ }{\mathrm{RfD}}_{\mathrm{d}}}$$(2) to analyze uncertainties and the sensitivity of risk factors in the health risk assessment. Assessment of PTEs in coastal settings is of great importance. The results of this study may provide valuable information for aquatic ecosystem protection, assurance of food safety, and preservation of human health in the future.

Methods

Study area descriptions

The Pangkajene dan kepulauan (Pangkep) regency is a suburban area located in the north of Makassar city, South Sulawesi, Indonesia within latitudes of 04°40′–08°00′ S and longitudes of 110°–119°48′67″ E (BPS 2021). Figure 1 presents a map of sampling sites. The Pangkep regency is approximately 51 km from the provincial capital of South Sulawesi, with a total area of 12,362.73 km² (11,464.44 km² of sea and 898.29 km² of land/terrestrial area). This area lies within the Maros Pangkep karst national park, which is an area of magnificent karst features in Indonesia with spectacular karst tower outcrops. Geologically, the late Eocene- to middle Miocene-age Tonasa limestone formation is the main geologic formation in this area, which comprises solid limestone, coral, wackestones, calcarenite, calcirudite, and bioclastic (Wilson 1996; Wilson and Bosence 1997; Ahmad and Hamzah 2016; Nuhung 2016) deposits. The uppermost lithologies in the formation comprise packstones, wackestones, and grainstones. The carbonate outcrops in the Tonasa formation were formed by large benthic foraminifera and sometimes by coralline algae (Wilson 1996; Wilson and Bosence 1997). The carbonate platform in Sulawesi is part of the Australian margin that experienced rifting beginning in the Jurassic period and is one of the main hydrocarbon reservoirs in Southeast Asia (Wilson 1996; Polvé et al. 1997; Wilson and Bosence 1997). Carbonate platform outcrops in the Pangkajene area are characterized by vertical tower karst features in coastal areas (Wilson and Bosence 1997). A report by UNESCO (2019) stated that the Maros–Pangkep geopark is underlain by the Bantimala Melange tectonic complex that comprises low-to-ultrahigh-grade metamorphic rocks, tectonic blocks of oceanic crust, and marine sedimentary rocks. Previous studies showed there are environmental degradations in the Maros Pangkep karst area which may harmful to the ecological system and human health due to cement production and limestone mining activities (WALHI 2018; Mallongi et al. 2019; Astuti et al. 2021a; Rauf et al. 2021a, 2021c; Mallongi et al. 2022; Rauf et al. 2022).

Figure 1. Map of sampling site (S for water and sediment of river; C for milkfish sampling; and A for shellfish sampling). Source: Author.

Hydrologically, this karst area has a high-capacity aquifer (100–500 L/s) (Nuhung 2016) that is dominated by subsurface drainage. Rainwater that falls on the limestone surface can pass through Dolina and Ponor and/or immediately infiltrate into rock cavities (Nuhung 2016). The aquifers and subsurface drainages in this area act as the catchment area for many rivers, including the Pangkajene, Pute, and Bantimurung rivers. The mainland is inhabited by a population of 345,775 (in 2020) dominated by people of Bugis–Makassar ethnicity who work in the livestock, agriculture, fishery, industry, mining, and tourism sectors (BPS 2021). The climate is characterized as a tropical monsoon climate (Astuti et al. 2021b): in 2020, the highest air temperatures occurred in October at 28.3 °C and the lowest air temperature occurred in March at 26.9 °C (BPS 2021). The amount of precipitation and rainy days in the Pangkep regency range from 8 to 966 mm/months and 3 to 27 days, respectively, in 2020 (BPS 2021). The soil in the Pangkep regency is highly fertile and is used to produce various crops and agricultural commodities such as rice, chili, shallots, garlic, spinach, watermelon, pomelo, mango, coconut, and medicinal plants (BPS 2021). In the fishery sector, milkfish is one of the main commodities in the Pangkep regency. Marble and limestone are the main mining resources in this area, although several minerals and other minable materials exist in the Pangkep regency, such as kaolin, basalt, coal, propylite, marble, clay/loam, limestone, feldspar, alluvial gold, gems, gravel, and radioactive minerals (Depdikbud 1976; DPU 2017; Astuti et al. 2021b, 2021c; Mallongi et al. 2022).

Sampling methods

This study was conducted in the Pangkajene dan Kepulauan (Pangkep) regency in South Sulawesi Province, Indonesia. The sampling was done in November 2020 and June 2021. A total of 18 samples of river water and 18 samples of river sediment, three samples of shellfish (Anadara granosa), and four samples of milkfish (Chanos chanos) were collected. The shellfish were taken from three sampling sites on the coast and they represent the biota most frequently consumed by residents. Additionally, we collected edible organisms (shellfish and milkfish) from coastal areas. Shellfish and milkfish make up the main foodstuffs in the Pangkep regency because they are cheap and abundantly available in that area. More broadly, milkfish is a major commodity in the Pangkep regency. Milkfish samples were taken from the two largest aquaculture fields in a downstream area of the Pangkajene river. River water and river sediment were collected twice, once in November 2020 (wet season) and once in June 2021 (dry season). Shellfish and milkfish were collected only once, during the month of harvest in June 2021.

The water samples were placed in high-density polyethylene (HDPE) bottles (1L). To sterilize equipment and prevent contamination, pre-cleaned bottle was prepared. The riverine water was collected using a water sampler from 10 to 30 cm below the water surface, whereas sediments were taken by Ekman grab from the sediment surface (10–30 cm depth). Approximately 500 g of sediment, 350 g of milkfish, and 500 g of shellfish samples were stored in clean polyethylene plastic, after which samples were stored in a cooler box with ice and directly transported to a laboratory.

Sediment analysis

All sediment samples were separated from rocks, grass, and other litter, and then oven-dried at 40 °C. All dried samples were crushed into powder and sieved through a 0.5-mm-mesh sieve. The samples were then ground by a blender into a fine powder and sieved using a 0.5-mm-mesh sieve. Afterward, 0.5 g of sediment was added to a solution of 5 mL 65% HNO₃ and 1 mL 60% HClO₄. This method complies with the established acid digestion method outlined by APHA (1999). Adding the HNO₃ and HClO₄ solution is necessary to digest silicate minerals or difficult-to-oxidize organic matter (OM) (APHA 1999). This method is also used as the established heavy-metal analysis protocol in Indonesia (Departemen Pertanian RI 2009). The digested samples were heated on a hot plate at 200 °C until they formed a clear ±3 mL solution. One milliliter of the clear solution was added to 25 mL distilled water, filtered, and homogenized.

Water sample analysis

A 5 mL water sample was added to 5 mL HNO₃ and 1 mL HClO₄. The acid digestion method was performed according to the APHA (1999) protocol and Indonesia’s standard for heavy metal analysis by Departemen Pertanian RI (2009). The solution was then heated on a hot plate at 200 °C until 1–3 mL of clear solution was formed. Then, 25 mL of distilled water was added to 1 mL of the clear solution.

Anadara granosa and Chanos chanos analysis

The flesh of Anadara granosa and Chanos chanos was ground using a blender, and 5 g of the ground flesh was added to a solution of 10 mL of 65% HNO₃ and 2 mL 60% HClO₄ and left overnight. Acid digestion was conducted according to the APHA (1999) protocol and Indonesia’s standard for heavy metal analysis by Departemen Pertanian RI (2009). The digested solutions were stirred and heated at 200 °C until a clear solution formed. After digestion, 1 mL of the clear solution was added to 25 mL of distilled water, filtered, and homogenized. Cd, Cr, Fe, and Pb concentrations were conducted using an AAS Thermo scientific iCE 3000 series instrument with wavelength absorption at 248.3 (Fe), 283.3 (Pb), 228.8 (Cd), and 357.9 (Cr).

Quality assurance

For accurate analysis, blanks and sample duplicates were included in the PTE analytical process. To sterilize equipment and prevent contamination, the glassware was properly precleaned by soaking in 6% HCl for at least 24 h and then rinsing three times with double-distilled water and oven-drying at a temperature of 105 °C. Analytical blanks were analyzed similarly as for sample analysis but without samples. The percent recovery achieved for each PTE was >90% with linear calibration curves (R² of 0.999).

Estimation of human health risk

Two exposure scenarios were considered in this study: (1)(1) $${\mathrm{HQ}}_{\mathrm{ingestion}-w\mathrm{ }}=\frac{C_{rw}\mathrm{ }\times \mathrm{ }{\mathrm{IR}}_{\mathrm{rec}-w}\mathrm{ }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ED}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{EV}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ET}}_{\mathrm{rec}}}{\mathrm{BW}\mathrm{ }\times \text{ AT }\times \mathrm{ }{\mathrm{RfD}}_{\mathrm{o}}}$$(1) a recreational scenario, which results from incidental ingestion and dermal contact when swimming in the Pangkajene river, and (2)(2) $${\mathrm{HQ}}_{\mathrm{dermal}-w}=\frac{C_{rw}\mathrm{ }\times \text{ SA }\times \mathrm{ }{K}_p\mathrm{ }\times \mathrm{ }{\mathrm{ET}}_{\mathrm{rec}}\mathrm{ }\times \text{ EV }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ED}}_{\mathrm{rec}-w}\mathrm{ }\times \mathrm{ }{\mathrm{CF}}_w}{\mathrm{BW}\mathrm{ }\times \text{ AT }\times \mathrm{ }{\mathrm{RfD}}_{\mathrm{d}}}$$(2) a residential scenario that arises from the consumption of shellfish and milkfish (Supporting Information Figure S1). When people are in recreational activities such as swimming or fishing, there is a potential for pollutant exposure through dermal contact with water and sediment (USEPA 2021a). They are also potentially exposed by PTE through incidental ingestion of water or sediment (USEPA 2015, 2021a; Canpolat et al. 2020). Due to the Pangkep population does not use the river water as the main drinking water resource, thus, PTEs exposures from river water and sediment were only included in the recreational exposure scenarios. Whereas, the health risks from shellfish and milkfish consumption were included in the residential exposure scenario.

The hazard quotient (HQ) and carcinogenic risk (CR) values were used in the present study to estimate the noncarcinogenic (Cd, Pb, Cr, and Fe) and carcinogenic (Pb, Cd, and Cr) risks, respectively, due to PTE exposure. Noncarcinogenic and carcinogenic health risks in the recreational exposure scenario were calculated using Eqs. (1)–(14) (USEPA 1989, 2011, 2015, 2021b, 2021c; ATSDR 2005; Shakeri et al. 2020):

Noncarcinogenic risks in the recreational exposure scenario: (1) $${\mathrm{HQ}}_{\mathrm{ingestion}-w\mathrm{ }}=\frac{C_{rw}\mathrm{ }\times \mathrm{ }{\mathrm{IR}}_{\mathrm{rec}-w}\mathrm{ }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ED}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{EV}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ET}}_{\mathrm{rec}}}{\mathrm{BW}\mathrm{ }\times \text{ AT }\times \mathrm{ }{\mathrm{RfD}}_{\mathrm{o}}}$$(1) (2) $${\mathrm{HQ}}_{\mathrm{dermal}-w}=\frac{C_{rw}\mathrm{ }\times \text{ SA }\times \mathrm{ }{K}_p\mathrm{ }\times \mathrm{ }{\mathrm{ET}}_{\mathrm{rec}}\mathrm{ }\times \text{ EV }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ED}}_{\mathrm{rec}-w}\mathrm{ }\times \mathrm{ }{\mathrm{CF}}_w}{\mathrm{BW}\mathrm{ }\times \text{ AT }\times \mathrm{ }{\mathrm{RfD}}_{\mathrm{d}}}$$(2) (3) $${\mathrm{HQ}}_{\mathrm{dermal}-S}=\frac{C_s\mathrm{ }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ED}}_{\mathrm{rec}-s}\mathrm{ }\times \text{ SA }\times \text{ AF }\times \mathrm{ }{\mathrm{ABS}}_{\mathrm{d}}\mathrm{ }\times \mathrm{ }{\mathrm{CF}}_s}{\mathrm{BW}\mathrm{ }\times \text{ AT }\times \mathrm{ }{\mathrm{RfD}}_{\mathrm{d}}}$$(3) (4) $${\mathrm{HQ}}_{\mathrm{ingestion}-S}=\frac{C_s\mathrm{ }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{rec}-s}\mathrm{ }\times \mathrm{ }{\mathrm{ED}}_{\mathrm{rec}}\mathrm{ }\times \text{ RBA }\times \mathrm{ }{\mathrm{IR}}_{\mathrm{rec}-s}\mathrm{ }\times \mathrm{ }{\mathrm{CF}}_s}{\mathrm{BW}\mathrm{ }\times \text{ AT }\times \mathrm{ }{\mathrm{RfD}}_{\mathrm{o}}}$$(4) (5) $$\text{Dermal RfD }=\mathrm{ }{\mathrm{RFD}}_{\mathrm{oral}}\mathrm{ }\times \mathrm{ }\mathrm{GIABS}$$(5) (6) $$\mathrm{HI}=\mathrm{ }{\mathrm{HQ}}_{\mathrm{Cd}}+{\mathrm{HQ}}_{\mathrm{Cr}}+{\mathrm{HQ}}_{\mathrm{Pb}}+{\mathrm{HQ}}_{\mathrm{Fe}}$$(6) (7) $$\mathrm{THI}={\mathrm{HI}}_{\mathrm{ingestion}}+{\mathrm{HI}}_{\mathrm{dermal}}$$(7)

Reference dose (RfD) and cancer slope factor (CSF) for dermal exposure were presented in Eqs. (5) and (12)(12) $$\text{Dermal CSF}=\raisebox{1ex}{${\mathrm{CSF}}_{\mathrm{oral}}$}\!\left/ \!\raisebox{-1ex}{$\mathrm{GIABS}$}\right.$$(12) (RAIS 2020). If Hazard quotient (HQ), Hazard Index(HI), and Total Hazard Index (THI) value >1 indicates that the adverse health consequences from PTEs exposure are likely to occur (USEPA 1989, 2011, 2015, 2021b, 2021c; ATSDR 2005; Shakeri et al. 2020). If the total carcinogenic risk (TCR), (Carcinogenic Risk of multiple PTEs (CR_m), and Carcinogenic risk (CR) value exceed 1 × 10⁻⁰⁴ indicates that the cancer is likely to occur due to the chronic exposure or the risk was unacceptable (USEPA 1991, 2005).

Carcinogenic risks in the recreational exposure scenario: (8) $${\mathrm{CR}}_{\mathrm{ingestion}-w}=\frac{C_{rw}\mathrm{ }\times \mathrm{ }{\mathrm{IR}}_{\mathrm{rec}-w}\mathrm{ }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ED}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{EV}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ET}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{CSF}}_{\mathrm{o}}}{\text{AT }\times \mathrm{ }\mathrm{BW}}$$(8) (9) $${\mathrm{CR}}_{\mathrm{dermal}-w}=\frac{C_{rw}\mathrm{ }\times \text{ SA }\times \mathrm{ }{K}_p\mathrm{ }\times \mathrm{ }{\mathrm{ET}}_{\mathrm{rec}}\mathrm{ }\times \text{ EV }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{rec}}\mathrm{ }\times \text{ ED }\times \mathrm{ }{\mathrm{CF}}_{\mathrm{w}}\mathrm{ }\times \mathrm{ }{\mathrm{CSF}}_{\mathrm{d}}}{\mathrm{BW}\mathrm{ }\times \mathrm{ }\mathrm{AT}}$$(9) (10) $${\mathrm{CR}}_{\mathrm{dermal}-S}=\frac{C_s\mathrm{ }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ED}}_{\mathrm{rec}-s}\mathrm{ }\times \text{ SA }\times \text{ AF }\times \mathrm{ }{\mathrm{ABS}}_{\mathrm{d}}\mathrm{ }\times \mathrm{ }{\mathrm{CF}}_{\mathrm{s}}\mathrm{ }\times \mathrm{ }{\mathrm{CSF}}_{\mathrm{d}}}{\mathrm{BW}\mathrm{ }\times \mathrm{ }\mathrm{AT}}$$(10) (11) $${\mathrm{CR}}_{\mathrm{ingestion}-S}=\frac{C_s\mathrm{ }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{rec}}\mathrm{ }\times \mathrm{ }{\mathrm{ED}}_{\mathrm{rec}}\mathrm{ }\times \text{ RBA }\times \mathrm{ }{\mathrm{IR}}_{\mathrm{rec}-s}\mathrm{ }\times \mathrm{ }{\mathrm{CF}}_{\mathrm{s}}\mathrm{ }\times \mathrm{ }{\mathrm{CSF}}_{\mathrm{o}}}{\mathrm{BW}\mathrm{ }\times \mathrm{ }\mathrm{AT}}$$(11) (12) $$\text{Dermal CSF}=\raisebox{1ex}{${\mathrm{CSF}}_{\mathrm{oral}}$}\!\left/ \!\raisebox{-1ex}{$\mathrm{GIABS}$}\right.$$(12) (13) $${\mathrm{CR}}_{\mathrm{m}}={\mathrm{CR}}_{\mathrm{Cd}}+{\mathrm{CR}}_{\mathrm{Cr}}+{\mathrm{CR}}_{\mathrm{Pb}}$$(13) (14) $$\mathrm{TCR}={\mathrm{CR}}_{\mathrm{ingestion}}+{\mathrm{CR}}_{\mathrm{dermal}}$$(14)

In dermal exposure, body surface area was calculated using follows equation Eq. (15)(15) $$SA=\frac{1}{6}{(BW\mathrm{ }\times \mathrm{ }H)}^{0.5}$$(15) (Reading and Freeman 2005): (15) $$SA=\frac{1}{6}{(BW\mathrm{ }\times \mathrm{ }H)}^{0.5}$$(15) where SA is the body surface area (m²), BW is the body weight (Kg), H represents body height (m). Then, SA is multiplied by 10,000 to convert in cm².

In residential exposure scenario, noncarcinogenic and carcinogenic health risk were estimated using Eqs. (16)–(21) (USEPA 1989, 2015, 2021b, 2021d):

Noncarcinogenic risks in the residential exposure scenario: (16) $${\mathrm{HQ}}_{\mathrm{ingestion}-f}=\frac{C_f\mathrm{ }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{res}-\mathrm{f}}\mathrm{ }\times \mathrm{ }{\mathrm{ED}}_{\mathrm{res}-f}\mathrm{ }\times \mathrm{ }{\mathrm{IR}}_{\mathrm{res}-f}}{\mathrm{BW}\mathrm{ }\times \text{ AT }\times \mathrm{ }{\mathrm{RfD}}_{\mathrm{o}}\mathrm{ }\times \mathrm{ }{10}^6}$$(16) (17) $$\mathrm{HI}=\mathrm{ }{\mathrm{HQ}}_{\mathrm{Cd}}+{\mathrm{HQ}}_{\mathrm{Cr}}+{\mathrm{HQ}}_{\mathrm{Pb}}+{\mathrm{HQ}}_{\mathrm{Fe}}$$(17) (18) $$\mathrm{THI}={\mathrm{HI}}_{\mathrm{milkfish}}+{\mathrm{HI}}_{\mathrm{Shellfish}}$$(18)

Carcinogenic risks in the residential exposure scenario: (19) $${\mathrm{CR}}_{\mathrm{ingestion}-f}=\frac{C_f\mathrm{ }\times \mathrm{ }{\mathrm{EF}}_{\mathrm{res}-f}\mathrm{ }\times \mathrm{ }{\mathrm{ED}}_{\mathrm{res}-f}\mathrm{ }\times \mathrm{ }{\mathrm{CSF}}_{\mathrm{o}}\mathrm{ }\times \mathrm{ }{\mathrm{IR}}_{\mathrm{res}-f}\mathrm{ }\times \mathrm{ }{10}^{-6}}{\mathrm{BW}\mathrm{ }\times \mathrm{ }\mathrm{AT}}$$(19) (20) $${\mathrm{CR}}_m={\mathrm{CR}}_{\mathrm{Cd}}+{\mathrm{CR}}_{\mathrm{Cr}}+{\mathrm{CR}}_{\mathrm{Pb}}$$(20) (21) $$\mathrm{TCR}={{\mathrm{CR}}_m}_{\left(\mathrm{milkfish}\right)}+{{\mathrm{CR}}_{\mathrm{m}}}_{\left(\mathrm{Shellfish}\right)}$$(21)

All abbreviations, units, and values related to the risk assessment (THQ, HI, CR, CR_m, TCR) equations were expressed in Table 1.

Table 1. Symbol, definitions, units, and values related to health risk assessment.

Symbols	Definition	Route of exposure		Unit	References
		Ingestion	Dermal
HQingestion-w	Noncarcinogenic risk via ingested of river water			Unitless	Site-specific
HQdermal-w	Noncarcinogenic risk from river water via dermal contact route			Unitless	Site-specific
HQdermal-s	Noncarcinogenic risk from river sediment via dermal contact route			Unitless	Site-specific
HQingestion- s	Noncarcinogenic risk from river sediment via ingestion route			Unitless	Site-specific
HQingestion-f	Noncarcinogenic risk via ingested food (shellfish, milkfish)			Unitless	Site-specific
HI	Hazard index			Unitless	Site-specific
THI	Total Hazard Index			Unitless	Site-specific
TCR	Total Cancer Risk			Unitless	Site-specific
CRingestion-w	Carcinogenic risk via ingested of river water			Unitless	Site-specific
CRingestion-f	Carcinogenic risk via ingested of food (shellfish, milkfish)			Unitless	Site-specific
CRdermal-w	Carcinogenic risk from river water via dermal contact route			Unitless	Site-specific
CRdermal-s	Carcinogenic risk from river sediment via dermal contact route			Unitless	Site-specific
CRm	Sum of carcinogenic risk of individual PTEs			Unitless	Site-specific
Crw	Concentration of PTEs in river water			mg/L	Site-specific
Cf	Concentration of PTEs in food samples (shellfish and milkfish)			mg/kg	Site-specific
Cs	Concentration of PTEs in river sediment			mg/kg	Site-specific
EFrec	Recreator exposure frequency	24		days/year	Site-specific
SA	Exposed surface skin area			cm^2	Site-specific
EDrec	Recreator exposure duration			years	Site-specific
EDres-f	Residential food sample exposure duration			years	Site-specific
EFres-f	Residential food sample exposure frequency			days/year	Site-specific
BW	Human body weight			kg	Site-specific
IRres-f	Ingestion rate of food samples			mg/day	Site-specific
EVrec	Recreator events		1	(events/day)	(USEPA 2021b)
ETrec	Recreator exposure time		Child: 0.54 Adult: 0.71	(hours/event)	(USEPA 2021b)
IRrec-w	Water ingestion in recreational exposure	Child:0.12 Adult:0.11	–	l/h	(USEPA 2015, 2021b)
IRrec-s	Sediment ingestion in recreational exposure	Child:200 Adult:100	–	mg/day	(USEPA 2015, 2021b)
RBA	Relative bioavailability factor		1	unitless	(USEPA 2021b)
AF	Adherence factor		Child: 0.2 Adult: 0.07	mg/cm^2	(USEPA 2015, 2021b)
ABSd	Skin absorption factor	–	0.001	unitless	(USEPA 2001, 2002)
Kp	Dermal permeability constant		1 × 10^-03 (Fe, Cd, Cr) 1 × 10^-04  (Pb)	cm/h	(USEPA 2004, 2021b)
GIABS	Fraction of contaminant absorbed in gastrointestinal tract		5 × 10^-02 (Cd) 1.3 × 10^-02(Cr) 1 (Fe and Pb)	unitless	(USEPA 2021b)
CFw	Volumetric conversion factor for water		1 × 10^-03	l/cm^3	(USEPA 1991, 2004)
CFS	Volumetric conversion factor for sediment		1 × 10^-06	kg/mg	(USEPA 1991, 2004)
RfD	Reference dose	Cd (water): 5 × 10^–04 Cd (food): 1 × 10^–03 Cr: 3 × 10 ^–03 Pb: 4 × 10^–03 Fe: 7 × 10^–01	Cd: 2.5 × 10^-05 Cr: 3.9 × 10^-05 Pb: 4 × 10^-03 Fe: 7 × 10^-01	mg/kg-day	(Barone et al. 2018; Zakir et al. 2020; USEPA 2021c)
CSF	Cancer slope factor	Cr: 4.2 × 10^–01 Cd: 15 Pb: 8.5 × 10^–03	Cr: 3.2 × 10^-01 Cd:3 × 10^+02 Pb: 8.5 × 10^-03	mg/kg-day	(Zakir et al. 2020; USEPA 2021c)

RFD dermal and CSF dermal obtained from $\text{Dermal RfD }=\mathrm{ }{\mathrm{RFD}}_{\mathrm{oral}}\times \text{GIABS and Dermal CSF}=\raisebox{1ex}{${\mathrm{CSF}}_{\mathrm{oral}}$}\!\left/ \!\raisebox{-1ex}{$\mathrm{GIABS}$}\right.$ (RAIS 2020)

Human data collection

Human data were obtained by interviewing 287 individuals, including adults and children, to obtain daily exposure pattern data used in the risk assessment metrics (ingestion rate (IR), body weight (BW), exposure frequency (EF), exposure duration (ED), surface area (SA), averaging time (AT), exposure time (ET), and exposure event (EV)). Data for this study were collected using proportional cluster random sampling from two village populations (Mappasaile and Tekolabbua villages).

Uncertainty and sensitivity analysis

The uncertainty and sensitivity analysis was conducted using Crystal Ball 11.1.2 (Oracle Inc Software, USA) in a Microsoft Excel (2019 version) environment. After estimating the HQ and CR, the MCS technique was run with 10,000 iterations to calculate THI and TCR, whereas considering the distribution of independent health risk variables in the study area (IR, BW, EF, ED, AT, ET, and EV) that were directly obtained from the interview process. A final human health risk result for each metal was produced by comparing the lower bound uncertainty (the 5th percentile) and the upper bound uncertainty (the 95th percentile) with the permissible value (<1 for HQ and <1 × 10⁻⁰⁶ for CR). In this study, the estimated values for HQ, CR, THI, and TCR are presented for the 5% and 95% percentiles. A sensitivity analysis was used to determine the most influential factor in the health risk estimations (Qu et al. 2018; Tajdar-Oranj et al. 2018). A high correlation coefficient indicates a greater influence on the final health risk calculation. Using USEPA human health risk assessment methods with MCS provides a probability distribution of HQ and CR values to estimate the uncertainty related to human health risks due to PTE exposure from various pathways (Qu et al. 2018).

Statistical analysis

IBM SPSS version 24 (SPSS Inc, USA) software was performed for statistical analysis. This study presented a parametric test result (at a significant level >.05). The statistical analysis was used to assess descriptive analysis (mean, standard deviation, minimum and maximum value). Then, the uncertainty and sensitivity tests were analyzed by Crystal Ball software (version 11.1.2).

Results and discussion

PTEs concentrations in water, sediment, and aquatic biotas

Tables 2 and 3 provide the concentration of selected PTEs (Cd, Cr, Fe, and Pb) in water, sediments, shellfish, and milkfish. The highest mean concentration in river water was found for Cr (1.64 mg/L), followed by Fe (1.31 mg/L), Pb (0.79 mg/L), and Cd (0.42 mg/L). According to Table 2, the mean concentration of PTEs in river water exceeded the water quality standards set by the WHO, USEPA, and the Indonesian standard, indicating that the water was highly polluted by PTEs and unacceptable as drinking water. Compared with world average concentrations, the PTE concentrations in the Pangkajene river were very high. Compared with prior studies by Aripai et al. (2012) and Salamahu (2012), the Pb and Cd concentrations in river water were higher than in previous studies, indicating that actions taken to control PTEs have not been fully successful in recent years. Cr and Pb concentrations in the Pangkajene river were lower than a river in India studied by Pandion et al. (2022); however, the Cd concentration in the Pangkajene river was higher than in the Indian river. High concentrations of PTEs may be influenced by a surplus amount of rainwater to the river system during wet season (Pandion et al. 2022). Aside from the factor of excess rainwater, anthropogenic factors such as untreated sewage disposal and direct industrial discharge to the river, as well as natural activities like underwater currents and sediment movement, may elevate PTE concentrations in the water column (Najmeddin et al. 2018; Pandion et al. 2022). Many anthropogenic activities take place in the area surrounding the Pangkajene river, such as limestone and marble mining; cement production; and domestic, agricultural, and fishery activities (Mallongi et al. 2022). Additionally, wastewater treatment remains rarely practiced in the Pangkep regency. These conditions may influence PTE accumulation in the Pangkajene river.

Table 2. Comparison of measured selected PTEs in River Water (RW) and River sediment (RS) with environmental quality criteria and world average concentrations.

Heavy metals	RW (N = 18)		RS (N = 18)		World average		Water quality criteria				SQGs^g
	Mean	95% UCL	Mean	95% UCL	Water^a	Sediment^b	Irrigation FAO ^c	Surface water USEPA^d	Drinking water WHO^e	Indonesia standards^f
Cd	0.42	0.67	BDL	BDL	2 × 10^-05	0.25	0.01	0.00072	0.003	0.003	3.53
Cr	1.64	2.03	67	74	1 × 10^-03	55.5	0.1	0.074	0.05	0.05	90
Fe	1.31	1.69	23,876	31,400	5 × 10^-03	50,300*	5	1	0.3	0.3	5000**
Pb	0.79	1.25	31	45	2 × 10^-04	48	5	0.0025	0.01	0.01	91.3

All concentration presented in mg.L^-1 for water and mg.kg^-1 for sediment; BDL: below detection limit.

^a Surface water world average concentration obtained from Klavinš et al. (2000).

^b World river sediment background concentration (Astatkie et al. 2021) *(Viers et al. 2009).

^c Standard for irrigation water by FAO (Ayers and Westcot 1985).

^d Standard for surface water by USEPA (2006).

^e Standard for drinking water by WHO (2017).

^f Water national standard for Indonesia (Ministry of health Republic Indonesia 2010).

^gSediment quality guidelines. PEL: probable effect limit (MacDonald et al. 2000; CCME 2001)**(Ameh et al. 2016).

Table 3. Comparison of mean selected PTEs in shellfish (Anadara granosa), milkfish (Chanos chanos) with food quality criteria.

PTEs	Shellfish (N = 3)	Milkfish (N = 4)	Food quality criteria
			FAO/WHO^a	EFSA^b	Korea standard^c	China standard^d	Indonesia standard^e
Cd	0.42	BDL	2^SF	0.05^F; 1^SF	0.1^F; 2^SF	0.1^F; 2^SF	0.1^F; 1^SF
Cr	1.99	1.74	–	–	–	2^F; 2^SF	–
Fe	129	20.2	–	48 ^F, SF	–	–	–
Pb	0.05	0.12	0.3^F	0.5^F; 1.5^SF	0.5^F; 2^SF	0.5^F; 1.5^SF	0.3^F; 1.5^SF

All concentration presented in mg.kg^-1 for shellfish, milkfish; SF: shellfish; F: fish.

^a Standard from FAO/WHO for contaminant in food (FAO/WHO 2019).

^b European Food safety Authority (EFSA) (Commission Regulation (EU) 2006; EFSA 2009, 2010, 2013).

^c MFDS (2017).

^d China Food and Drug Administration (2017).

^e Indonesia national standard for food contaminant (BSNI 2009).

The mean concentration of Cd, Cr, Fe, and Pb in sediments of the Pangkajene river followed the order: Fe > Cr > Pb > Cd. The Cd concentration was lower than the detection limit in the sediment column, indicating that Cd mainly occurs in the aqueous phase in the river ecosystem and is readily available to aquatic organisms. This finding is inconsistent with a study by Maddusa and Asrifuddin (2008), which reported higher Cd concentrations in sediment than in the water. This condition may be influenced by the chemical properties of Cd, which is known as a labile PTE that migrates rapidly within the environment (Jiang et al. 2013). Several studies have demonstrated that Cd is easily transported into water is highly bioavailable to aquatic organisms (Jiang et al. 2013; Liu et al. 2019). Cd, Cr, and Pb concentrations in sediment were lower than the probable effect level (PEL) value (Table 2). When PTE concentrations in sediments are lower than the PEL, adverse effects on benthic organisms will be infrequent (Kuang et al. 2021).

Fe in sediment was higher than the PEL value, indicating that harmful effects may be expected to occur frequently in sediment-dwelling benthic organisms. High concentrations of PTEs in the sediment may result from the deposition of suspended materials containing PTEs and downstream water movement (Yi et al. 2011). The concentration of Pb in this study was higher than that in prior studies (Salamahu 2012; Fitriani et al. 2013, 2014; Ali 2017), and the Fe concentration in this study was also higher than that reported in an earlier study by Amina (2012). A study by Paena et al. (2015) reported that sediment in the Pangkajene river contained a high concentration of OM and phosphate, which might influence the accumulation of PTEs in the river ecosystem. Compared with results reported by Yenny et al. (2020), Pb and Cr concentrations in the Pangkajene river sediment were higher than those in the Citarum river. As the Citarum river is among the most polluted rivers in Indonesia, these findings demonstrate an alarming state of contamination in the Pangkajene river.

Table 3 lists the mean PTE concentrations in shellfish (Anadara granosa) and milkfish (Chanos chanos) from the Pangkajene river. Based on the mean concentrations, the order of PTEs in shellfish samples was Fe > Cr > Cd > Pb, and the order in milkfish samples was Fe > Cr > Pb > Cd. The Cd concentration in shellfish in this study was higher than that reported in prior studies by Maddusa and Asrifuddin (2008) and Haspullah et al. (2018). Pb and Cr concentrations in shellfish in the present study are also higher than those in shellfish studied by Haspullah et al. (2018). This result reveals that Cd, Cr, and Pb concentrations in Anadara granosa in the years of this study are higher than in the prior studies, indicating that PTE pollution in the Pangkajene river is becoming increasingly severe in recent years.

In comparison with other studies, Fe and Pb concentrations in shellfish from the Pangkajene river were higher than in shellfish from the Java sea and Madura straits (Yona et al. 2020, 2021). Cd and Cr concentrations in shellfish studied here were higher than those in a study by Soegianto et al. (2020), whereas Cd and Pb concentrations in milkfish were lower than those in previous studies (Syarif 2015; Zulfiah et al. 2017; Haeriah 2019). A study by Awaluddin et al. (2020) showed that pond water and sediments in the Pangkep regency had high Pb concentrations of 0.0182 mg/L and 25.210 mg/kg, respectively. A high concentration of Pb in pond water and sediment may influence the PTE concentration in milkfish (Awaluddin et al. 2020).

The concentrations of PTEs in shellfish and milkfish shown in Table 3 indicate that all PTE concentrations in shellfish and milkfish were lower than the food quality criteria values set by EFSA, except for Fe. Aquatic organisms such as fish regulate their intake of trace elements from water via intake of suspended foods and ion transfer through lipophilic membranes (Yi et al. 2011), whereas bottom-feeder organisms like Anadara granosa take up nutrients and contaminants from sediments (Mrozińska and Bąkowska 2020; Soegianto et al. 2020). Hence, the high concentration of PTEs in sediments and water contribute to bioaccumulation in aquatic organisms.

Point estimate of human health risk

Table 4 reports the exposure pattern of Pangkajene communities, with noncarcinogenic indicator values shown in Table 5. All HQ values were below 1 in both exposure scenarios, except for the HQ_ingestion of Cr in the residential exposure scenario. This indicates that chronic exposure to Cr through milkfish and shellfish consumption can potentially induce adverse effects and noncarcinogenic risks to humans in the future (HQ > 1). This result is inconsistent with other studies (Bandara and Pathiratne 2019; Mwakalapa et al. 2019; Pandion et al. 2022) that found HQ values lower than 1. Based on the HI value in the recreational scenario, PTE (Cd, Cr, Fe, and Pb) exposure from both ingestion and dermal routes was safe from noncarcinogenic health effects. This result is consistent with the findings of several other studies (Alidadi et al. 2019; Canpolat et al. 2020; Shakeri et al. 2020). Based on the study by Paustenbach et al. (2003), dermal exposure poses an insignificant health risk due to the minor amount of Cr that can penetrate deep skin layers. Another study stated that speciation of PTEs plays a role in health risk estimations because it influences the bioavailability, water-soluble properties, and the mobile fraction of PTEs in the human body (Sah et al. 2017). For example, Cr(VI) is more toxic than Cr(III), because it can be absorbed into deep skin layers (Paustenbach et al. 2003; Alidadi et al. 2019). Thus, dermal contact may make a small contribution to total health risks. Additionally, a study by Tong et al. (2021) demonstrated that ingestion is the primary exposure route of PTEs in an aquatic system because the values of HQ_ingestion of PTEs were higher than those of HQ_dermal for both children and adults.

Table 4. Human exposure characteristics in the coastal community of Pangkep regency, Indonesia.

Descriptive	Statistics	Population
		Adults (N = 200)	Children (N = 87)
Sex	n (%)
Men		75 (37.5)	37 (42.5)
Women		125 (62.5)	50 (57.5)
Age (years)^a	Mean ± SD	35 ± 12	11 ± 4
	Range	19 − 72	5 − 18
Body weight (BW) (kg)	Mean ± SD	56 ± 8.5	31 ± 11.1
	Range	29 − 79	12 − 68
Height (H) (cm)	Mean ± SD	157.9 ± 8.4	131.7 ± 15.1
	Range	133 − 178	99 − 165
Exposure duration (ED) (years)	Mean ± SD	35 ± 12	11 ± 3
	Range	19 − 72	5 − 18
Exposure frequency (EF) (days/year)
Shellfish (Anadara granosa)	Mean ± SD	116.4 ± 88.8	135.6 ± 73.1
	Range	12 − 365	48 − 365
Milkfish (Chanos chanos)	Mean ± SD	206.4 ± 76.5	142.7 ± 46.4
	Range	48 − 365	75 − 240
Surface skin area (SA) (cm^2)	Mean ± SD	15,613 ± 1463	10,435 ± 2371
	Range	11,123–18,714	5774–17,170
Ingestion rate (IR)
Shellfish (Anadara granosa) (mg/day)	Mean ± SD	231,875 ± 97,498.3	179,816 ± 79,311.2
	Range	44,000–660,000	60,000–396,000
Milkfish (Chanos chanos) (mg/day)	Mean ± SD	207,000 ± 72,279.8	141,436.7 ± 44,759.7
	Range	30,000–360,000	75,000–240,000

^a Based on Indonesia’s regulation, people under 19 years are categorized as children.

Table 5. Noncarcinogenic risk of PTEs exposure in the Pangkajene’s coastal community (N = 287).

Exposure settings	Environmental media	HQ-Cd (Mean ± SD)				HQ-Cr (Mean ± SD)				HQ-Fe (Mean ± SD)				HQ-Pb (Mean ± SD)				HI (Mean ± SD)				THI (Mean ± SD)
		Ing		Derm		Ing		Derm		Ing		Derm		Ing		Derm		Ing		Derm
		A	C	A	C	A	C	A	C	A	C	A	C	A	C	A	C	A	C	A	C	A	C
Recreational Settings (mean ± SD)	River water	8 × 10^-02 ± 1 × 10^-02	1 × 10^-01 ± 5 × 10^-02	2 × 10^-01 ± 2 × 10^-02	2 × 10^-01 ± 3 × 10^-02	2 × 10^-01 ± 3 × 10^-02	3 × 10^-01 ± 9 × 10^-02	6 × 10^-01 ± 4 × 10^-02	5 × 10^-01 ± 6 × 10^-02	2 × 10^-04 ± 3 × 10^-05	3 × 10^-04 ± 1 × 10^-04	2 × 10^-05 ± 2 × 10^-06	2 × 10^-05 ± 3 × 10^-06	2 × 10^-02 ± 3 × 10^-03	3 × 10^-02 ± 1 × 10^-02	3 × 10^-04 ± 2 × 10^-05	3 × 10^-04 ± 3 × 10^-05	3 × 10^-01 ± 4 × 10^-02	4 × 10^-01 ± 1 × 10^-01	8 × 10^-01 ± 8 × 10^-02	7 × 10^-01 ± 9 × 10^-02	1 × 10^+00 ± 1 × 10^-01	1.2 × 10^+00 ± 2 × 10^-01
	River sediment	NC	NC	NC	NC	3 × 10^-03 ± 5 × 10^-04	1 × 10^-02 ± 4 × 10^-03	2 × 10^-03 ± 2 × 10^-04	8 × 10^-03 ± 1 × 10^-03	4 × 10^-03 ± 7 × 10^-04	2 × 10^-02 ± 6 × 10^-03	4 × 10^-05 ± 3 × 10^-06	2 × 10^-04 ±3 × 10^-05	9 × 10^-04 ± 2 × 10^-04	4 × 10^-03 ±1 × 10^-03	1 × 10^-05 ± 7 × 10^-07	4 × 10^-03 ± 1 × 10^-03	8 × 10^-03 ± 1 × 10^-03	3 × 10^-02 ± 1 × 10^-02	2 × 10^-03 ± 2 × 10^-04	8 × 10^-03 ± 1 × 10^-03
Residential Settings (mean ± SD)	Shellfish	5 × 10^-01 ± 4 × 10^-01	9 × 10^-01 ± 6 × 10^-01	NC	NC	8 × 10^-01 ± 7 × 10^-01	1 × 10^+00 ± 9 × 10^-01	NC	NC	2 × 10^-01 ± 2 × 10^-01	4 × 10^-01 ± 2 × 10^-01	NC	NC	2 × 10^-02 ± 1 × 10^-02	3 × 10^-02 ± 1 × 10^-02	NC	NC	1.6 × 10^+00 ± 1 × 10^+00	3 × 10^+00 ± 2 × 10^+00	NC	NC	3.5 × 10^+00 ± 1.7 × 10^+00	4,6 × 10^+00 ± 2.1 × 10^+00
	Milkfish	NC	NC	NC	NC	1 × 10 ^+00 ± 6 × 10^-01	1 × 10^+00 ± 8 × 10^-01	NC	NC	6 × 10^-02 ± 3 × 10^-02	6 × 10^-02 ± 4 × 10^-02	NC	NC	5 × 10^-01 ± 3 × 10^-01	5 × 10^-01 ± 3 × 10^-01	NC	NC	1.8 × 10^+00 ± 9 × 10^-01	2 × 10^+00 ± 1 × 10^+00	NC	NC

A: Adult; C: children; Ing: Ingestion route; Derm: dermal contact route; NC: Not calculated; HQ: Hazar quotient; HI: Hazard Index; THI: Total Hazard Index; SD: standard deviation.

Generally, humans that are exposed to more than one PTE are vulnerable to adverse health impacts (Pandion et al. 2022). Therefore, a cumulative risk assessment (HI and THI) must be conducted to determine the cumulative effects of PTEs. The order of HI_ingestion values decreased as shellfish > milkfish > river water > river sediment, whereas HI_dermal values due to river water exposure were higher than those of HI_dermal values from river sediment exposure. In the recreational exposure scenario, the THI value was greater than 1, suggesting that adverse health effects may potentially occur in people who swim in the Pangkajene river due to incidental ingestion of and dermal contact with river water and sediments containing PTEs. The HQ, HI, and THI values in children are higher than in adults (Table 5), which indicates that children are more at risk than adults. This result is similar to that of another study by Han et al. (2021). This result is also supported by several reports mentioning that children are more susceptible to exposure to water containing PTEs than adults (Gao et al. 2019; Xiao et al. 2019; Canpolat et al. 2020; Tong et al. 2021). This difference may be caused by their physiological immaturity, as well as their unprotected behavior (Creel 2002; Bose-O'Reilly et al. 2010; Al osman et al. 2019; Karatela et al. 2020). Furthermore, the exposure of children to pollutants is greater in terms of proportional body weight, and enduring long-term adverse effects may result from early exposure (Creel 2002; Sly and Carpenter 2012). Different metabolic rates in children also increase their susceptibility to illness; moreover, exposure to some chemicals at a young age when organs are still growing and developing appears to be more harmful than at older ages (Etzel 2020).

The carcinogenic risk indicators are presented in Table 6. In the recreational exposure scenario, the concentration of Cd in river water significantly contributed to carcinogenic risk (CR > 1 × 10⁻⁰⁴). Like the noncarcinogenic risk, the contribution of river sediment exposure to carcinogenic risk is small. This result is consistent with the findings of several other studies (Wojciechowska et al. 2019; Yang et al. 2019; Ustaoğlu et al. 2020). Based on the CR_m value, exposure to river water through incidental ingestion and dermal contact is not safe (CR_m > 1 × 10⁻⁰⁴). This finding is contrary to that of a previous study by Canpolat et al. (2020), which stated that there is no carcinogenic risk of PTE exposure through recreation activities. Conversely, exposure to river sediment is still deemed safe (CR_m < 1 × 10⁻⁰⁶). The CR, CR_m, and TCR values tend to be higher in adults than in children. As demonstrated in a prior study (Tong et al. 2021), this trend illustrates that adults are more susceptible to carcinogenic effects of PTE exposure from water systems.

Table 6. Carcinogenic risk of PTEs exposure in the Pangkajene’s coastal community (N = 287).

Exposure settings	Environmental media	CR-Cd (Mean ± SD)				CR-Cr (Mean ± SD)				CR-Pb (Mean ± SD)				CRm (Mean ± SD)				TCR (Mean ± SD)
		Ing		Derm		Ing		Derm		Ing		Derm		Ing		Derm
		A	C	A	C	A	C	A	C	A	C	A	C	A	C	A	C	A	C
Recreational settings	River water	3 × 10^-04 ± 1 × 10^-04	1 × 10^-04 ± 3 × 10^-05	8 × 10^-04 ± 3 × 10^-04	2 × 10^-04 ± 6 × 10^-05	3 × 10^-05 ± 1 × 10^-05	2 × 10^-05 ± 3 × 10^-06	3 × 10^-06 ± 1 × 10^-06	1 × 10^-06 ± 2 × 10^-07	3 × 10^-07 ± 1 × 10^-07	1 × 10^-07 ± 3 × 10^-08	4 × 10^-09 ± 1 × 10^-09	1 × 10^-09 ± 3 × 10^-10	3 × 10^-04 ± 1 × 10^-04	2 × 10^-04 ± 3 × 10^-05	8 × 10^-04 ± 3 × 10^-04	2 × 10^-04 ± 6 × 10^-05	1 × 10^-03 ± 4 × 10^-04	4 × 10^-04 ± 8 × 10^-05
	River sediment	NC	NC	NC	NC	2 × 10^-06 ± 6 × 10^-07	2 × 10^-06 ± 4 × 10^-07	1 × 10^-08 ± 5 × 10^-09	1 × 10^-08 ± 4 × 10^-09	2 × 10^-08 ± 6 × 10^-09	2 × 10^-08 ± 4 × 10^-09	2 × 10^-10 ± 6 × 10^-11	2 × 10^-10 ± 4 × 10^-11	2 × 10^-06 ± 6 × 10^-07	2 × 10^-06 ± 4 × 10^-07	1 × 10^-08 ± 5 × 10^-09	1 × 10^-08 ± 4 × 10^-09
Residential Settings (mean ± SD)	Shellfish	4 × 10^-03 ± 3 × 10^-03	2 × 10^-03 ± 1 × 10^-03	NC	NC	5 × 10^-04 ± 4 × 10^-04	3 × 10^-04 ± 2 × 10^-04	NC	NC	3 × 10^-07 ± 2 × 10^-07	1 × 10^-07 ± 9 × 10^-08	NC	NC	4 × 10^-03 ± 4 × 10^-03	2 × 10^-03 ± 2 × 10^-03	NC	NC	5 × 10^-03 ± 4 × 10^-03	3 × 10^-03 ± 2 × 10^-03
	Milkfish	NC	NC	NC	NC	7 × 10^-04 ± 4 × 10^-04	2 × 10^-04 ± 1 × 10^-04	NC	NC	1 × 10^-06 ± 6 × 10^-07	3 × 10^-07 ± 2 × 10^-07	NC	NC	7 × 10^-04 ± 4 × 10^-04	2 × 10^-04 ± 1 × 10^-04	NC	NC

A: Adult; C: children; Ing: Ingestion route; Derm: dermal contact route; NC: Not calculated; CR_m: Carcinogenic risk from combined metals; TCR: total cancer risk; SD: standard deviation.

In the residential exposure scenario, the order of CR_shellfish decreased as Cd > Cr > Pb, whereas the order of CR_milkfish decreased as Cr > Pb > Cd. Based on the CR_m value, the consumption of shellfish and milkfish is not safe because it is potentially associated with carcinogenic effects in humans (CR_m > 1 × 10⁻⁰⁴). Thus, action to reduce PTE concentrations in the river ecosystem is required immediately. The TCR values in the recreational and residential scenarios indicate that adults have a higher carcinogenic risk than children. These findings further support the idea that cancer vulnerability increases in midlife and at older ages (White et al. 2014). Cancer development is a complex process; nevertheless, the life course approach can be used to investigate the influence of prenatal and early life exposure on cancer in adults (White et al. 2014; Bhatt 2019). Age can reflect the ED and accumulation of CR factors; additionally, a multifactor process of CR may influence changes in normal cell processes that lead to cancer, including DNA damage accumulation and mutation over time.

Probabilistic risk assessment

Using a probabilistic risk approach based on MCS, the mean, 5th, and 95th percentile values of the THI and TCR distributions for different population groups are shown in Figure 2. In the recreational exposure scenario, the mean THI values estimated by the probabilistic approach for adults and children were 1.81 and 1.75, respectively (Figure 2(A)), whereas in the residential scenario, the mean THI values calculated using MCS were 3.05 (adult) and 3.97 (children). Based on those values, both children and adults were at risk of noncarcinogenic health problems related to PTE exposure (THI > 1).

The THI values for adults and children in either exposure scenario were greater than 1 at the 95th percentile, indicating that 95% of the different age group populations experienced noncarcinogenic risk from multiple exposure pathways and that noncarcinogenic risk may not have occurred in 5% of the population (Sanaei et al. 2021). For noncarcinogenic risk, the sensitivity test results (Figure 3) revealed that the exposure frequency to milkfish (EF-MF) is the main factor influencing noncarcinogenic risk for adults in the residential scenario, with a contribution of 31.00%. Exposure frequency to shellfish (EF-SF) was the main factor in total noncarcinogenic risk in children, with a contribution of 30.90%. In the recreational exposure scenario, ED as the main factor related to noncarcinogenic risk for the adult population, with a contribution of 35.10%, and the Cr concentration in river water (Cr-RW) contributed most to noncarcinogenic risk in child populations, with a contribution amounting to 22.4%.

Figure 2. Cumulative probability of THI (A) and TCR (B) through combined pathways. THI: total hazard index; TCR: total cancer risk.

Figure 2(B) presents the cumulative probability value for estimated TCR in recreational and residential scenarios. In the recreational exposure scenario, the mean values for adults and children using a probability risk approach are 1.12 × 10⁻⁰³ and 3.98 × 10⁻⁰⁴, respectively. In the residential exposure scenario, the mean values for adults and children are 5.41 × 10⁻⁰³ and 3.08 × 10⁻⁰³, respectively. Those values showed that both in the recreational and residential scenarios TCR values were higher than 1 × 10⁻⁰⁴, indicating that a potential CR exists from multiple PTE exposure pathways in the Pangkep coastal communities. Figure 4 depicts the TCR value sensitivity analysis results. Exposure frequency to shellfish is the most influential factor for both adult and child populations in the residential scenario, with contributions of 67.7% and 45.6%, respectively. In the recreational scenario, ED is the most important factor for adult and child populations, with contributions of 74.2% and 33.5%, respectively. This result is in line with a study by Gao et al. (2019).

Figure 3. Sensitivity results for THI value in residential (A), and in recreational receptors (B); the result of Monte Carlo Simulation, Total Hazard Index (THI) defined as a forecast value, and the assumptions include PTEs concentration in river water (RW), in river sediment (RS), milkfish (MF) and shellfish (SF), Ingestion rate (IR), exposure frequency (EF), Body weight (BW), Exposure duration (ED).

Figure 4. Sensitivity results for TCR value in residential (A), and in recreational receptors (B); the result of Monte Carlo Simulation, Total Cancer Risk (TCR) is defined as a forecast value, and the assumptions include PTEs concentration in river water (RW), river sediment (RS), milkfish (MF), and shellfish (SF), Ingestion rate (IR), exposure frequency (EF), Body weight (BW), Exposure duration (ED).

Risk management

The 95th percentile value represents the highest exposure that is reasonably predicted to occur at the site and is known as the reasonable maximum exposure (RME) (USEPA 2001). An RME value that exceeds the target level risk or the allowable risk means that implementation of risk reduction measures is needed. Based on the equation by Ditjen (2012), a recommended value for restricting shellfish consumption (EF-SF: 3 days/year for adults and EF-SF: 7 days/year for children) should be put in place to avoid carcinogenic risk. Aside from limiting shellfish consumption, several studies recommend implementing a well-balanced diet to avoid chronic diseases such as cardiometabolic disease and death (Zhai et al. 2015; Micha et al. 2017). A recent review by Zhai et al. (2015) stated that the consumption of vegetables, fruits, and other edible plants containing vitamins and essential metals can reduce the toxicity of metals in the human body. Vitamins C and E are antioxidants that have the benefit of scavenging free radicals and decreasing lipid peroxidation. For the recreational scenario, limiting ED may protect the population from carcinogenic risk with recommended ED values of 13 years (adults) and 9 years (children).

To protect populations from noncarcinogenic risks, reducing milkfish consumption frequency (EF-MF) to 170 and 140 days/year for adults and children, respectively, must be implemented. Additionally, reducing the Cr concentration in river water needs to be implemented immediately. A study by Yoshinaga et al. (2018) recommends using a magnesium (Mg)- and iron (Fe)-based hydrotalcite-like compound as a low-cost and highly effective depurative method to reduce Cr pollution in the river. Additionally, strong regulatory actions, PTE concentration monitoring in river ecosystems, as well as the use of wastewater treatment plants, should be performed by the local authority.

Conclusions

The mean value of PTE concentrations in river water was found to be above the water quality standard set by the WHO, indicating that the river water is highly polluted and unacceptable for daily consumption purposes. Except for Fe, the mean PTE concentrations in sediments were lower than the PEL values, indicating that negative effects on sediment-dwelling benthic organisms are not expected to occur frequently. The mean PTE values in the aquatic organisms (Anadara granosa and Chanos chanos) were below the limit for food quality standards, except for Fe concentrations in shellfish. Based on THI and TCR values, the coastal area communities of the Pangkep regency are at high risk of noncarcinogenic and carcinogenic effects from multiple PTE exposure pathways. This conclusion is also supported by the cumulative risk value determined using the Monte Carlo simulation, which demonstrates mean values of THI and TCR value above the allowable values (THI > 1 and TCR > 1 × 10⁻⁰⁴). The sensitivity test results revealed that ED and the concentration of Cr in river water (Cr-RW) are the most influential factors in noncarcinogenic risk in the recreational scenario, whereas the consumption frequency of milkfish and shellfish were the greatest noncarcinogenic and carcinogenic risk factors in the residential scenario. Thus, we recommend reducing Cr concentrations in the river ecosystem, restricting swimming durations, and limiting the consumption frequency of shellfish and milkfish to overcome future health risks.

Author’s contributions

All authors have materially participated and have approved the final article to publish. Ratna Dwi Puji Astuti: conceptualization, data curation, writing original draft and review, edit, data analysis; Anwar Mallongi: conceptualization, review manuscript, supervised the project; Kyungho Choi: critical feedback and helped shape the research, review manuscript; Ridwan Amiruddin: review manuscript, referencing; Muh Hatta: Review Manuscript, referencing; Kraichat Tantrakarnapa: contribute to final version of the manuscript, referencing; Annisa Utami Rauf: data collecting, draft editing.

Competing interest

The authors declared that there is no conflict of interest

Declaration of submission

This work has not been published previously and/or not under consideration for publication elsewhere. We declare that all authors were agree will not published the manuscript elsewhere if it accepted in the same form, in English or in any other languages, including electronically without the written consent of the copyright-holder.

Human ethical statement

This study has passed the ethical test with protocol number 28920093024 issued by the health research ethics commission, Hasanuddin University

Acknowledgements

We would like to thank the Pangkajene dan kepulauan (Pangkep) government for the warm welcome during this study occurs. The appreciation also goes to Dr. Sarinah Basri K, S.K.M, M.Kes, and Zulfikar S.Si., M.M. for their contribution during the sampling process.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability

The datasets obtained and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

Additional information

Funding

This study funded by the Ministry of Research and Technology of the Republic of Indonesia (DIKTI) through PKPI-PMDSU 2021 scheme [Grant Number: 172.5/E4.4/KU/2021].