Prevalence and Intensity Effects of Anisakidae Nematode on Eastern Baltic Cod (Gadus morhua Linnaeus, 1758) Condition Factors and Energy Reserves

Abstract

Over the past few decades, the population of cod in the Eastern Baltic has faced numerous challenges due to environmental changes, overfishing, and predation, as well as the effects of infection by third-stage larvae of the Anisakidae parasite in the liver. The aim of this study was to estimate the prevalence and infection level of Anisakidae nematodes in the Eastern Baltic cod stock over a five-year period and analyze the effect of infection on cod health condition. A total of 1946 samples of the Eastern Baltic cod (Gadus morhua) were collected and tested for the presence of Anisakidae nematode larvae. All nematodes found in livers were identified as Anisakidae with an overall prevalence of 30.9%, a mean infection density of 0.8 (median 0.4) nematodes per gram of liver tissue, and a range of 0.01–29.2 nematodes per gram. The prevalence of infection tended to increase with the age of the fish. In multivariate analysis, increasing infection intensity decreased the odds of cod having good Fulton’s and Clark’s condition scores and a hepatosomatic index (HSI) above the population average. While our study shows a clear Anisakidae effect on Fulton’s and Clark’s condition scores and the HSI, these indicators could also be influenced by other environmental, physiological, and pathological factors.

1. Introduction

Eastern Baltic cod (Gadus morhua) is a demersal marine coastal fish species that feeds on invertebrates and smaller fish, including Atlantic herring (Clupea harengus membras) and sprat (Sprattus sprattus balticus) [1,2]. Although related to the Atlantic cod, it represents a genetically distinct cod population adapted to the brackish environment of the Eastern Baltic Sea [3]. Over the last decade, the Eastern Baltic cod stock has experienced a collapse, with stock parameters such as size structure, size at maturity, and stock distribution at their lowest levels [4]. In this period, the body condition of the Baltic cod has been declining, and an increase in parasitic nematode abundance has been observed [4]. The marine environment is dynamic, and the factors contributing to the current state of the cod stock have been multifactorial. For example, increasing temperatures due to climate change exacerbate Baltic Sea eutrophication, which leads to hypoxia that affects both adult cod and the health and survival of their offspring [5]. Low oxygen levels in water also disrupt the food web and can reduce prey availability to the cod [6,7]. Overfishing and predation have further impacted population growth and hindered the population’s ability to recover [1,5,8]. Despite the implementation of fishing restrictions in the European Union (EU), the recovery of the cod stock has not improved [5,9]. However, environmental pressures and fishing practices do not fully explain the severity of the population decline, suggesting additional stressors that may be contributing to the poor condition of the stock [4].

In studies surrounding fish population ecology, the effects of parasites are often overlooked or treated as a separate issue, even though numerous studies have shown that parasitic infections, especially Anisakidae, can substantially affect cod condition, population-level mortality, and community [4,10,11,12]. In the Eastern Baltic Sea, the predominant species of Anisakidae nematodes is Contracaecum osculatum. Its increasing prevalence and infection intensity in recent decades have coincided with the growth of the Baltic grey seal (Halichoerus grypus) population, which is the definitive host of the parasite [4,13]. Historically, C. osculatum and Anisakis simplex have been reported in 1994, in the southern Baltic Sea (subdivisions (SD) 25 and 26), where the C. osculatum prevalence in cod livers was 2.57% (78/3036), but that of A. simplex was 0.92% (28/3036) [14]. However, in more recent studies, the prevalence of C. osculatum has increased and varies between 13–89% in the Baltic Sea subdivisions 22, 24, and 25 [10]. Additionally, multiple studies have shown that liver infection with C. osculatum third-stage larvae can decrease cod health and mortality. Histopathological investigations reveal that infected livers exhibit extensive tissue damage, inflammation, and a reduction in the fat content of hepatocytes [15]. As a result, chronic liver disease can develop, impairing digestive functions and reducing the nutritional condition of the fish [11,16]. An experimental study revealed that, even when provided with increased amounts of food, heavily infected cod exhibited impaired growth and increased mortality compared with lightly infected or uninfected individuals [17].

This study aims to determine the prevalence and infection pressure of Anisakidae nematodes in Eastern Baltic cod over a five-year period and to assess the effect of infection on the health condition of the cod.

2. Materials and Methods

2.1. Sample Collection and Biological Data

In total, 1946 samples of the Eastern Baltic cod (whole fish or liver) were collected in the Baltic Sea’s International Council for the Exploration of the Sea (ICES) subdivisions (SD) 26 and 28 (Figure 1) in winter (December) and spring (March) from 2018 to 2022 during the Baltic International Trawl Survey (BITS) and in May of 2020 during Baltic International Acoustic Survey (BIAS). The total length of the fish (cm), wet weight and eviscerated weight (g), liver weight (g), sex, maturity stage, and age were recorded for all freshly caught fish. All fish with a total length of more than 15 cm (TL) were put in the freezer (−20 °C) until further analyzed for the presence of parasites.

Sex and maturity stages were determined by visual inspection of the gonads using a 6-index scale [18]. According to the six stages of gonad maturation, the following maturity stages were determined: immature (stage 2), ripe (stage 3), mature (stage 4), spawning (stage 5), and spent (stage 6). The age of cod was established by counting annual growth zones in the sagitta otoliths according to the method described in the Manual for the Baltic Cod Age Reading [19]. The broken and burned otoliths were read under a binocular microscope in reflected light.

2.2. Body Condition and Energy Reserves

The cod condition was calculated using Fulton’s body condition factor K to determine the relationship between weight and length of the fish to determine the condition of similar size and growth fish [20] and Clark’s condition factor that is better suited for comparing fish across different size classes to quantify growth patterns by relating its weight to its length to evaluate its nutritional state and overall health in a population [21].

Fulton’s body condition factor K was estimated as follows:

F = 100 × W/L³,

where W is the weight (g), and L is the total length (cm).

Clark’s condition factor was calculated as follows:

C = 100 × W/L³,

where W is the eviscerated weight of the fish (g), and L is the length of the fish (cm).

The Hepatosomatic index (HSI) was calculated to determine the metabolic status of the liver [22]

HSI was calculated as follows:

HSI = (liver weight/total weight) × 100.

2.3. Parasitological Analyses

Liver samples were thawed at room temperature before the examination. Entire liver samples < 10 g (n = 767) were compressed between two glass slides and examined under a stereomicroscope Nikon SMZ1000 (Nikon Coorporation, Tokyo, Japan) (15–20× magnification). Larvae from whole liver samples that were >10 g (n = 1179) were recovered through the artificial digestion method described in the Standard Operating Procedure by Istituto Superiore di Sanità, 2021 [23]. All visible nematodes were removed from the compressed liver or digested material and, where possible, identified based on typical morphology–anteriorly directed intestinal caecum, that goes along the preventriculus, posteriorly directed ventricular appendix, that runs along the intestine, a tooth, that is located between the lateroventral lips at the cephalic end, and a tail, that terminates without a spine or mucron [24,25]. If morphological identification was not possible, the nematodes were recorded at the family level as Anisakidae.

2.4. Data Analysis

Prevalence and percentages defined the presence of parasites, and infection intensity was expressed by the number of nematodes per liver (e.g., all visible larvae were counted in the liver) [26]. Density was expressed as the number of nematodes per gram of liver tissue to compensate for differences in nematode numbers related to liver size [11]. A cod was considered infected if at least one Anisakidae was present.

Descriptive statistics and univariate analysis were calculated and summarized using IBM SPSS Statistics (v. 22.0). To minimize the effect of season on condition factors and HSI, data were stratified and analyzed in two separate groups: spring (fish caught in March–May) and winter (caught in December). Median, mean values, and interquartile ranges were used to represent average infection intensities. Mean values, standard deviations, and ranges were used to characterize central tendency in age, morphometric measurements, condition factors, and HSI. Median values of age, morphometric measurements, condition factors, and HSI were compared using Mood’s median test. The chi-square test and Fisher’s exact test were used to test for associations between infection prevalence and demographic and morphometric data. The Spearman rank correlation test was used to test for an association between cod age and infection intensity. The Klopper–Pearson method was used to estimate 95% confidence intervals in OpenEpi (v.2.3.1) [27]. Two-tailed p < 0.05 was considered statistically significant.

Forward and backward logistic regression analyses were conducted, selecting models with the lowest Akaike information criterion (AIC) [28] values, including corrected AIC (AICc), as determined by the performance package’s performance function for the fitted generalized linear models (GLMs) with a binomial family. Model selection adhered to the underlying assumptions, with multicollinearity assessed using the vif function from the car package [29]. The response (dependent) variable was either good or bad for Fulton’s condition factor (values ≥ 1 were considered “good,” values < 1 were considered “bad” based on reference values by Dutil 1995 [30] or above or below the study population average for Clark’s condition factor and HSI. The significance of each independent variable was assessed using the summary function or analysis of deviance (type III tests) from the car package [29]. A result was considered statistically significant at p < 0.05, while a p < 0.1 was considered a trend and was further investigated. Tjur’s coefficient of discrimination (Tjur’s R²) was calculated from the performance package, function performance, to assess how much the particular model explains the probability of having a good or bad Fulton coefficient or above or below average HSI or Clark’s condition factor. We decided to perform logistic regressions, as this was an epidemiological study aimed at qualitatively assessing the condition of cod, which also allowed us to calculate odds ratios (ORs). Moreover, we also performed ANCOVA. However, the data failed to comply with the assumptions even after log transformation. Nevertheless, the obtained statistics were qualitatively similar. All the figures and statistics were performed in R (v.4.3.2) [31]. Group-wise distributions of condition indices and hepatosomatic index were visualized as violin plots with overlaid boxplots using ggplot2.

3. Results

3.1. Eastern Baltic Cod Population

From 2018 to 2022, 77.4% (n = 1507) of samples were collected in ICES subdivision 28, and 22.6% (n = 439) came from ICES subdivision 26 (Figure 1). Most of the cod in the study population were caught in spring (March and May)—55.6% (n = 1082) and were male—62.1% (n = 1208). In 2.7% (n = 53) of cases, it was impossible to determine the sex. Differences were observed in sex distributions between seasons, and in spring, the proportion of male fish was 69.6% (n = 727), and female fish was 30.4% (n = 332), but in winter, the distribution was more equal: 56.7% (n = 481) were male fish, and 43.3% (n = 353) were female fish.

Cod obtained in spring were older than in winter (p < 0.05) (

Table 1. Eastern Baltic cod age distribution, morphometric measurements, liver weight, HSI, Fulton’s and Clark’s condition factor indices in different study seasons, 2018–2022.

Variables	Spring			Winter
	N	Mean (SD *)	Range	N	Mean (SD *)	Range
Age, years	1082	3.1 (1)	1–7	862	2.2 (1.1)	0–6
Wet weight, g	1082	265.5 (213.4)	1–1800	864	203.8 (162.5)	1–1904
Gutted weight, g	1057	214.5 (167.1)	26–1510	834	179.3 (135.4)	30–1531
Length, cm	1082	28.7 (7.4)	6–60	864	26.4 (7.1)	4–58
Liver weight, g	1059	10.9 (11.6)	0.1–92.4	832	10.9 (11.2)	0.5–133.6
Mean HSI	1058	3.5 (1.9)	0.2–23.4	832	4.7 (1.7)	0.7–10.1
Fulton’s coefficient	1082	0.9 (0.1)	0.6–1.4	864	0.9 (0.1)	0.5–1.6
Clark’s coefficient	1057	0.7 (0.1)	0.3–0.9	834	0.8 (0.1)	0.5–1.2

* SD: standard deviation.

). Mean HSI and Clark’s coefficient values in winter tended to be higher than in spring (p < 0.05). However, such a difference was not observed with Fulton’s condition factor (p = 0.07) (Table 1). Liver weight did not differ between the two seasons (p = 0.4), but the gutted weight of fish caught in spring was significantly higher than in winter (p = 0.02) (Table 1).

3.2. Anisakidae Nematode Prevalence in Eastern Baltic Cod

Overall prevalence of Anisakidae nematodes in cod liver was 30.9% (n = 602; 95% CI: 28.9–33). In 244 cases (40.5%, 95%CI: 36.5–44.6), the species could not be determined; therefore, the nematodes were identified at the Anisakidae family level. The prevalence of Anisakidae infection tended to increase significantly with age (p < 0.05) (

Table 2. Prevalence of Anisakidae nematodes in Eastern Baltic cod by sex, age group, length, season, year, and ICES subdivision.

Variable (n)		Prevalence % (n)	95% CI	p-Value
Sex (1893)	Male (1208)	34.3 (414)	31.6–37	<0.05
	Female (685)	27.4 (188)	33.6–42.3
Age (1944)	1 (229)	3.5 (8)	1.5–6.8	<0.05
	2 (627)	18.5 (116)	15.5–21.2
	3 (644)	31.5 (203)	27.9–35.3
	4 (292)	60.9 (178)	55.1–66.6
	5 (112)	77.6 (87)	68.8–85
	6 (18)	88.9 (16)	65.3–98.6	N/A
	7 (2)	100.0 (2)	N/A
Length (1946)	≤30 cm (1301)	17.9 (233)	15.9–20.1	<0.05
	<30 cm (645)	57.2 (369)	53.3–61.1
Season (1944)	Spring (1082)	37.7 (404)	34.8–40.6	<0.05
	Winter (864)	23.4 (198)	20.6–26.4
Year (1944)	2018 (100)	30.0 (30)	21.2–39.9
	2019 (438)	32.6 (143)	28.3–37.3
	2020 (346)	28.9 (100)	24.2–34	0.7
	2021 (436)	29.6 (129)	25.3–34.1
	2022 (626)	32 (200)	29.5–37.1
ICES subdivision (1946)	26 (439)	37.4 (164)	32.8–42.1	0.001
	28 (1507)	29.1 (438)	26.8–31.4

). Male cod were more frequently infected with Anisakidae than female cod (p < 0.05) (Table 2). A higher infection prevalence was observed in cod from ICES SD26 (p = 0.001).

Cod infected with Anisakidae had significantly lower median Fulton’s and Clark’s condition factors (p < 0.05); however, the difference in numerical values was marginal (Figure 2 and Figure 3). The presence of infection did not affect median HSI values (p = 0.2) (Figure 4) (Table 1).

3.3. Anisakidae Nematode Infection Intensity and Density in Eastern Baltic Cod

Median infection intensity was three worms per liver with a range of 1–113, and median infection density was 0.4 worms/g liver tissue with a range of 0.01–29.2 (

Table 3. Infection intensities and densities of Anisakidae in Eastern Baltic cod livers by sex, age group, season, year, and ICES subdivision.

Variable (n)		Median Infection Intensity (Nematodes per Liver)	IQR 2	p-Value	Median Infection Density (Nematodes/g Liver Tissue)	IQR	p-Value
Sex (1893)	Male (1208)	3	1–8.3	0.8	0.4	0.17–1.1	<0.05
	Female (685)	3	1–10		0.2	0.1–0.5
Age (1944)	1 (229)	1	1–1	<0.05	0.3	0.2–0.5
	2 (627)	1	1–2		0.5	0.2–1
	3 (644)	2	1–5		0.2	0.1–0.6
	4 (292)	5	2–11		0.4	0.1–0.9	0.001
	5 (112)	13	5–28		0.7	0.2–1.5
	6 (18)	24	11.7–47		0.5	0.3–1.1
	7 (2)	59	10,108 1		0.6	0.3–0.8
Season (1944)	Spring (1086)	3	1–10	0.08	0.4	0.2–1.1	<0.05
	Winter (868)	2	1–70		0.3	0.1–0.5
Year (1944)	2018 (100)	1	1–2.5	0.03	0.2	0.1–0.5
	2019 (438)	2	1–8		0.2	0.1–0.5
	2020 (346)	3	1–8.5		0.2	0.1–0.5	<0.05
	2021 (436)	5	2–15.5		0.4	0.1–0.8
	2022 (626)	3	1–6		0.7	0.3–1.4
ICES subdivision (1946)	26 (439)	5	1–113	0.001	0.6	0.03–29	<0.05
	28 (1507)	2	1–108		0.3	0.01–6

¹ Only 2 data entries, range; ² interquartile range (IQR).

). There was a moderate positive correlation between the infection intensity and the age of the fish (r_s = 0.6, p < 0.05). Cod collected in ICES SD26 had higher infection intensities than cod collected in SD28 (p < 0.05) (Table 3).

3.4. Multivariate Analysis by Fitting Generalized Linear Models (GLMs)

3.4.1. Fulton’s Condition Factor in Winter and Spring

For winter, the final model for Fulton’s condition factor (classified as “good” or “bad”) in cod with the lowest AIC values (AIC: 783.815, AICc: 784.083) was established by both forward and backward selection. Factors included in the model were collection year, ICES SD, maturity, infection density, and age, all of which were statistically significant (

Table 4. Multivariate model results for Anisakidae infection factors and cod health indicators (Fulton’s condition factor, Clark’s condition factor, and HSI) across seasons.

Cod Health Indicator	Season	Factor	LR Chisq	Df	p-Value
Fulton’s condition factor (good or bad)	Spring	Maturity	21.1	3	<0.001
		Year	19.7	3	<0.001
		Infection density	3.8	1	0.05
		ICES subdivision	10.4	1	0.001
		Sex	6.1	1	0.01
		Age	4.1	1	0.04
	Winter	Year	71.2	4	<0.001
		ICES subdivision	19.5	1	<0.001
		Maturity	6.1	2	<0.05
		Infection density	11.6	1	<0.001
		Age	4.4	1	0.04
Clark’s condition factor (above or below average)	Spring	Year	28.2	3	<0.001
		Sex	24	1	<0.001
		ICES subdivision	18.8	1	<0.001
		Infection density	16.3	1	<0.001
		Age	12.3	1	<0.001
	Winter	ICES subdivision	41.7	1	<0.001
		Infection density	17.2	1	<0.001
		Age	17.1	1	<0.001
		Year	14.4	4	0.006
HSI (above or below average)	Spring	Maturity	76.9	3	<0.001
		Year	51.8	3	<0.001
		Sex	49.4	1	<0.001
		Age	35.7	1	<0.001
		ICES subdivision	14.3	1	<0.001
		Infection density	11.8	1	<0.001
	Winter	Year	162.1	4	<0.001
		Age	17.8	1	<0.001
		ICES subdivision	14.1	1	<0.001
		Maturity	8.1	3	0.04
		Infection density	2.4	1	0.1

Abbreviations: LR Chisq—likelihood ratio chi-squared test; Df—degrees of freedom.

). The final model explained 14% (Tjur’s R²) of the variation in having either a good or a bad Fulton’s condition factor. Fulton’s condition varied between the years, with the odds of fish caught in 2022 being in better condition 4.3 times higher (95% CI: 2.2–8.7) than in 2018. The odds of cod caught in ICES SD28 having a good Fulton’s condition factor were 4.1 times (95% CI: 2.1–8.5) higher than cod from ICES SD26. Ripening fish (maturity stage 3) were 1.6 times more likely to be in better condition than immature (stage 2) fish. However, the difference was insignificant compared to fish in maturity stages 4 and higher (OR = 3.2, 95% CI: 0.8–12.2). The odds of fish having a good Fulton’s condition score decreased with age (OR = 0.8, 95% CI: 0.6–0.9) and increasing infection density (OR = 0.2, 95% CI: 0.1–0.6).

For spring, the final model for Fulton’s condition factor (classified as good or bad) in cod with the lowest AIC values (AIC: 1132.449, AICc: 1132.704) was established by backward selection. Factors included in the model were maturity, year, infection density, ICES SD, sex, and age, where all of them except infection density were statistically significant (Table 4). The final model explained 10% (Tjur’s R²) of the variation in having either a good or a bad Fulton coefficient.

Fulton’s condition varied between the odds of fish caught in 2022 and 2020 being in better condition, 2.5 (95% CI: 1.5–4.3) and 2.1 (95% CI: 1.2–3.6) higher than in 2018. The odds of cod caught in ICES SD28 having a good Fulton’s condition factor were 1.9 times (95% CI: 2.1–8.5) higher than in cod from ICES SD26. In spring, ripening and mature (stage 3 and stage 4), cod were 2.8 (95% CI: 1.2–7.8) and 5.3 (95% CI: 2–15.9) times more likely to be in better condition than immature fish. In spring, female cod were 1.8 times (95% CI: 1.1–2.8) more likely to be in good condition than males. The conditions also improved with age, with OR being 1.21 (95% CI: 1–1.5).

3.4.2. Clark’s Condition Factor in Winter and Spring

For winter, the final model for Clark’s condition factor (classified as above or below average) in cod with the lowest AIC values (AIC: 1028.677, AICc: 1028.852) was established by both forward and backward selection. Factors included in the model were ICES SD, age, infection density, and collection year, all of which were significant (Table 4). The final model explained 15% (Tjur’s R²) of the variation in having Clark’s index, which was classified above or below the study population average.

Similar to Fulton’s condition factor, Clark’s condition factor also varied over the years, with cod caught in 2022 having 1.9 times greater odds (95% CI: 1.1–3.5) of having Clark’s condition factor above average than cod caught in 2018. The odds of cod from ICES SD28 having a Clark’s condition factor above the average (0.7) were 4.4 times higher (95% CI: 2.7–7.3) than for cod caught in ICES SD26. Increasing age and infection density decreased the odds of cod having a Clark’s condition score above the study’s population average (OR 0.7, 95% CI: 0.6–0.8, and OR 0.2, 95% CI: 0.1–0.5, respectively).

For spring, the final model for Clark’s condition factor (classified as above or below average) in cod with the lowest AIC values (AIC: 1340.695, AICc: 1340.833) was established by both forward and backward selection. Factors included in the model were ICES subdivision, year, infection density, sex, and age, and all of them were statistically significant (Table 4). The final model explained 11% (Tjur’s R²) of the variation in having Clark’s condition factor, which was either above or below the average.

The odds of cod from ICES SD28 having Clark’s condition factor above the average (0.7) were two times higher (1.5–2.8) than those caught in ICES SD26. Increasing age and infection density decreased the odds of cod having a Clark’s condition factor above the study population average (OR = 0.8, 95% CI: 0.7–0.9, and OR = 0.7, 95% CI: 0.5–0.8, respectively). In spring, female fish were 2.1 times (95% CI: 1.5–2.8) more likely to have Clark’s condition factor above average than male fish.

3.4.3. HSI in Winter and Spring

For winter, the final model for the HSI (classified as above or below average) in cod with the lowest AIC values (AIC: 891.161, AICc: 891.336) was established by both forward and backward selection. Factors included in the model were year, age, ICES SD, and infection density, all of which were statistically significant except infection density (Table 4). The final model explained 30% (Tjur’s R²) of the variation in having an HSI above or below the population average.

Compared to 2018, over the years, the cod were more likely to have an HSI below the study’s population average, with cod caught in 2022 having 47 times (95% CI 21.6–112.2) higher odds of having a worse HSI. Fish caught in SD28 had fewer odds of having an HSI below the population average than fish caught in SD26 (OR = 0.4, 95%CI 0.2–0.6). Older fish were less likely to have an HSI below the population average than younger fish (OR = 0.7, 95% CI: 0.6–0.8).

For spring, the final model for the HSI (classified as above or below average) in the cod with the lowest AIC values (AIC: 936.324, AICc: 936.579) was established by both forward and backward selection. Factors included in the model were year, sex, maturity, age, ICES SD, and infection density, all of which were statistically significant (Table 4). The final model explained 42% (Tjur’s R²) of the variation in having an HSI, either above or below the average.

Compared to 2019, over the years, cod were more likely to have an HSI below the study population average, with cod caught in 2021 and 2022 having 3.8 (95% CI 2.3–6.6) and 3.7 (95%CI 2.2–6.5) higher odds of having an HSI below the study population average. Cod caught in SD28 had less odds (OR = 0.5, 95% CI 0.3–0.7) of having an HSI below the population average than fish from SD26. Older fish were less likely to have an HSI below the population average than younger fish (OR = 0.6, 95% CI: 0.5–0.7). Female cod were less likely to have an HSI below the population average than male fish (OR: 0.2; 95% CI: 0.1–0.3). The odds of HSI being below the population average were higher in mature (stage 4; OR = 1.2, 95% CI: 0.5–2.5) and spent (stage 6; OR = 35.7, 95% CI: 9.7–175.3) fish than in immature fish (stage 2). Increasing infection density increased the odds of cod having an HSI value below the population average (OR = 1.6, 95% CI: 1.2–2.2).

4. Discussion

With the increasing prevalence of Anisakidae larval infections reported in the Eastern Baltic cod population over the past few decades, the focus of many recent research efforts has been on determining whether, and to what extent, these parasites affect the cod’s health [4,31,32]. Most currently published studies have focused on Baltic cod collected in ICES subdivisions 24–26 [10,15,16,32,33,34,35,36]. In contrast, the present study provides important and comprehensive insights into the prevalence, infection intensity, density, and effects of Anisakidae nematodes on cod health in the Eastern Baltic Sea, specifically in SD26 and SD28.

Because the fish livers were frozen and were processed using the artificial digestion method before examination, the recovered nematodes could be identified at the family level (Anisakidae). While all three Anisakidae species of public health importance have been previously reported in the Baltic Sea cod, there is a geographical delineation of the species distribution: Anisakis spp. and Pseudoterranova decipiens are more commonly found in the Central and Southern Baltic Sea, whereas the larval infections with Contracaecum spp. dominate in the East [32,33,36]. This could be because Contracaecum spp. have adapted to lower salinity conditions, which, in comparison, can negatively impact the survival of P. decipiens and Anisakis simplex larvae [37,38]. This hypothesis was further confirmed by reports of Contracaecum spp. being the predominant anisakid infection in the stomachs of Baltic grey seals near the Swedish, Polish, and Latvian coastlines, and that the larvae have been found in other fish species in the Bothnian Bay [39,40,41,42]. Although molecular identification was not performed, the geographical origin of the samples suggests that the observed anisakid larvae were most likely Contracaecum spp.

Overall, the prevalence of Anisakidae in the present study was 30.9%, with a mean infection intensity of eight larvae per liver and a range of 1–113. At first glance, this was a significantly lower rate than reported in the Eastern Baltic cod population from 2016 to 2020, where the estimated prevalence was 88–100%, and mean infection intensity ranged from 29 to 33 nematodes per cod liver [4]. However, the data are not directly comparable because the article by Eero et al. [4] only included data from fish with a length of 30 cm and above in the analysis. In contrast, this study analyzed fish longer than 15 cm. Additionally, the prevalence of anisakid nematodes in cod liver from ICES SD24–SD26 ranged from 3.4–22.5% when young fish (1–2 years old) and adult (3+ years old) fish were analyzed together [36]. Nevertheless, our study clearly shows that anisakid prevalence and intensity tended to increase with both age and length, while infection density had no effect, which could be due to changes in cod liver mass throughout the years, which could dilute the density of larvae per gram [4]. Among cods older than four years, 60.9% of fish were infected, and 57.2% of fish that were longer than 30 cm were positive for Anisakidae larvae. These findings were also observed with data from ICES SD25, where Contracaecum sp. larvae were either absent or had very low prevalence in juvenile cod (6–29 cm), but both prevalence and infection intensity increased in larger cod (total length 31–48 cm) [34].

The life expectancy of C. osculatum larvae in cod liver is at least two years, and these nematodes tend to accumulate in the liver as the fish ages [33,34,43]. This happens due to changes in dietary preferences—juvenile cod mainly feeds on benthic organisms, such as crustaceans, whereas larger cod primarily feed on herring and sprat [1,44]. All these prey groups can serve as paratenic hosts for Anisakidae larvae, allowing cod to acquire infections throughout their development [17]. Previous reports on C. osculatum prevalence and infection intensities in sprat were from 1 to 16%, and intensity ranged from 1 to 13 larvae per fish in the Southern Baltic Sea [45,46,47]. Experimental research on crustaceans as paratenic hosts to C. osculatum has reported that not all the host animals survive long after ingestion of larvae, which could explain why infection prevalence and intensity in yearling cod in this study were significantly lower than in other age classes [47].

There was a significant difference in Anisakidae infection prevalence between ICES SD26 and 28 (37.4% and 29.1%, respectively). Spatial patterns in cod liver infection rates with Anisakidae nematodes have been observed in the Western and Southern Baltic Sea [32,35,36]. Contracaecum osculatum prevalence tends to increase eastwards, corresponding to the areas with lower salinity gradients [35,48]. Grey seals, the final hosts of Contracaecum spp., are the source of infection to cod, especially in areas where the feeding and hunting grounds of the two species overlap [34,46]. Based on available grey seal haul-out data in the Baltic Sea, there are more grey seal colonies in SD28 than in SD26, which could suggest higher Contracaecum spp. exposure risk to cod and consequently higher prevalence in SD28, which contradicts the results of this study [49]. The reason for this is partly because accurately assessing grey seal population density is not possible; although feeding and foraging site fidelity exists, grey seals are migratory species that can travel great distances [48,49,50]. A more likely explanation for the varying infection rates between the subdivisions could be due to the migratory nature of cod itself: depending on the season, the fish caught in any of the subdivisions might have had different prior exposure to parasite infection, making it difficult to assess the actual regional effect on the parasite infection prevalence in fish [1,36].

In this study, male cod had significantly (p < 0.05) higher Anisakidae prevalences than female cod—34.3% and 27.4%, respectively. While the proportion of individuals of the same species infected with parasites varies between the sexes, there are two possible causes: ecological (different life histories, eating habits, or areas they inhabit have higher loads of parasitic larvae) or hormonal (testosterone in some species can lower immunity, males tend to be more aggressive and defend territory) [51]. The difference in parasite prevalences could also be explained by skewed sex ratios in the study: during spring, there were twice as many male fish recruited than in winter, when the proportion was closer to 1:1. Similar observations have been made in the Atlantic cod studies in Canada and Norway and this was attributed to the time of cod recruitment: during spawning male cod tend be more stationary, while female cod deposit eggs and then move to deeper waters than males [52,53,54]. A study on cod in the Southern Baltic Sea found Anisakidae infection prevalence and intensities to be higher in female cod than in male cod. Still, the differences were not statistically significant [36]. In that study, the authors argued that males were smaller than females and, therefore, less likely to be infected [36]. In the Eastern Baltic cod population, the results of univariate and multivariate analysis indicate that focusing solely on parasite infection while ignoring physiological and environmental factors that affect cod condition and energy reserves may lead to conclusions that exaggerate the parasite infection’s effect.

In our study, using the multivariable model, infection density proved to be a significant factor in predicting whether cod would have good or bad Fulton’s condition factor, and the odds of cod having Clark’s condition coefficient and HSI above or below the study population average. Similar results have been reported by Ryberg et al. (2020) [11], who analyzed a total number of 152 cod (length range 30–53 cm) captured in the East of Bornholm and found that Fulton’s condition factor decreased significantly with increasing infection density and that the same negative impact was observed in physiological markers related to liver functions. GLM analyses performed by Horbowy et al. [34] reported that with the increase of 20 parasites, Fulton’s condition score decreased by 0.01. In addition, Mohamed et al. (2020) [16] revealed a significant negative correlation between the infection intensity of C. osculatum larvae and muscle mass. A recent article published by ICES SD25–26 on cod found that body condition factors and HSI decreased with increasing infection density [32]. These observations demonstrate that when evaluating the effects of Anisakidae infection in cod, recording infection intensity and density data is crucial, as prevalence alone may not accurately assess body condition. Furthermore, the age (or, in studies where age is not determined, length) distribution also matters. In our dataset, cod from age classes 1–7 were included, providing a more comprehensive view of Anisakidae infection dynamics across various ages. In contrast, other studies have chosen a subpopulation of cod of a particular length because younger cod have lower prevalence, infection intensities, and densities. Therefore, when the population is viewed as a whole, the effect of Anisakidae larvae on the values of condition factors and HSI could be diluted [11].

It is worth noting that an interesting observation was made when GLMs were fitted to assess the impact of Anisakidae intensity and density alongside other factors on cod condition factors and HSI. Infection intensity, expressed as the number of nematodes per liver, had no significant effect in the models. In contrast, infection density (number of nematodes per gram of liver tissue) did. In recent publications, one or the other method has been used to describe infection, but not both simultaneously [11,16,32,34]. Ryberg et al. (2020) [11] argued that infection density data removed the impact of fish’s age and liver size and gave a better overview of the larval saturation in the liver tissue. Despite this, there was a drawback—the weight of cod liver changes over the year. Therefore, depending on the season, when the cod was caught, and the maturity stage of the fish, the value of infection density will change [55]. Therefore, seasonal effects on liver mass should be considered in studies where cod is collected during different months of the year and over many years. When average values of Fulton’s and Clark’s condition scores were compared between seasons and maturity stages in this dataset, no such differences were observed (

Table A1. Age, morphometric measurement, liver weight, HSI, Fulton’s coefficient, and Clark’s coefficient distributions based on the maturity index of the fish and the season.

Season	Maturity Index (n)	Mean Age, Years (SD)	Mean Length, cm (SD)	Mean Wet Weight, g (SD)	Mean Gutted Weight, g (SD)	Mean Liver Weight, g (SD)	Mean HSI (SD)	Mean Fulton’s Coefficient (SD)	Mean Clark’s Coefficient (SD)
Spring	1 (23)	1 (0)	9.7 (1.9)	8.4 (4.5)	N/A	N/A	N/A	0.8 (0.1)	N/A
	2 (90)	2.7 (1.1)	27 (7.7)	218.6 (212.8)	183.3 (176.3)	9.7(10.5)	4.1 (1.2)	0.9 (0.1)	0.7 (0.1)
	3 (287)	3.3 (1)	30.3 (6.6)	288.9 (195.1)	235.2 (159.6)	13.5 (11.1)	4.4 (1.5)	0.9 (0.1)	0.7 (0.1)
	4 (479)	3.3 (1)	30.9 (6.5)	318.8 (216.5)	249.2 (165.5)	12.9 (12.4)	3.8 (1.7)	0.9 (0.1)	0.7 (0.1)
	5 (8)	3.8 (1)	33.6 (9.3)	469.3 (548.1)	318.3 (338.9)	14.8 (17)	3.2 (0.9)	1 (0.1)	0.7 (0.1)
	6 (195)	2.5 (0.7)	23.5 (4.5)	143.6 (131.3)	109.3 (114.3)	2.2 (3.8)	1.5 (1.9)	1 (0.1)	0.7 (0.1)
Winter	1 (28)	0	7.1 (1.5)	3.7 (1.9)	N/A	N/A	N/A	0.9 (0.2)	N/A
	2 (448)	2 (1)	25.3 (6.2)	173.6 (145.4)	149.4 (124.4)	8.8 (10.4)	4.4 (1.7)	0.9 (0.1)	0.8 (0.1)
	3 (372)	2.6 (0.9)	28.9 (5.5)	248.9 (165.5)	211.2 (137.6)	13.3 (11.3)	5 (1.6)	0.9 (0.1)	0.8 (0.1)
	4 (6)	2.5 (0.8)	29 (3.7)	248.9 (94.8)	200 (74.4)	13.6 (5.1)	5.5 (0.3)	0.9 (0.1)	0.8 (0.04)
	6 (8)	4 (1.1)	36.6 (6.5)	414.4 (237.3)	353.1 (199.4)	20.4 (20.3)	4.4 (1.6)	0.8 (0.2)	0.7 (0.1)

, Appendix A), and this may be because cod first uses up energy reserves in the liver and only then muscles [32].

Besides Anisakidae larval density in the liver, other factors in the final model significantly affected condition scores and liver indices. The year of sampling was an important factor across all seasons, as substantial year-to-year variation was observed in the odds of cod exhibiting good or poor Fulton’s condition factor or having Clark’s condition factor and HSI values above or below the population average. This could be because the marine environment is not static and, therefore, each year represented a combination of specific conditions in the Baltic Sea that could have impacted the cod, for example, water temperature, availability of food, especially during the post-spawning period, salinity, water saturation with oxygen, pollution, fishing/by-catch, and hunting by seals [5]. Exposure to hypoxia has been linked to deteriorated body condition in Eastern Baltic cod, and it also negatively affects organisms in the food web, thereby causing a food shortage for cod [6,56].

The maturity stage of the fish was a significant factor influencing Fulton’s condition score and HSI, particularly in the spring. There was seasonal variability in the Eastern Baltic cod’s weight, condition, and energy reserves: in autumn and winter, more feeding occurs in preparation for spawning in spring, when most of the energy is expended [55,56]. During the last two decades, the spawning time of Eastern Baltic cod shifted from spring (March–April) to summer (May–July) [4]. Since Fulton’s condition factor considers the whole weight of the fish, the improved condition might be related to the increased gonadal weight rather than the improved condition score [20,57]. This was reflected clearly in the Clark’s condition factor analysis, where only gutted weight was considered; as a result, maturity no longer had an effect in the final model. Seasonal variability in condition factors and HSI, along with fluctuations in population structure between spawning and feeding grounds at different times of the year, may also help explain why cod from ICES SD28 had higher odds of exhibiting a good Fulton’s condition factor, Clark’s condition factor, and HSI values above the population average compared with cod from ICES SD26 [1,55]. In spring, the odds for female cod to be in better nutritional condition and to have an HSI above the population average were higher than for male cod, while the food consumption in both sexes is suppressed during spawning. Still, in the wild, males establish spawning areas, are more stationary than females, and participate in spawning for longer periods than female cod, which also means going for extended periods without food [58].

5. Conclusions

Anisakidae larvae density in the cod liver can predispose the Eastern Baltic cod to lowered condition factors and HSI. Still, such conclusions should be made with caution, primarily when referring to wild populations. Our data indicate that various ecological and biological factors may also influence changes in cod condition and energy reserves, and these should be considered when conducting future studies. A causal graph of these factors based on the literature review and study data is shown in Appendix B. It is also important to point out that Anisakidae larvae are not the only parasites found in abundance in cod. To get a better idea of the complex web of factors that affect the well-being of the Eastern Baltic cod population, subsequent studies should focus not only on ecology, biology, and Anisakidae larval infections in cod but also consider the presence of other parasite species and other hepatic abnormalities, such as toxicopathic lesions.