Does bigger mean sicker? A systematic review and meta-analysis of the intraspecific relationship between host body size and parasite infection across vertebrate taxa

Elucidating the determinants of parasite infection levels of individuals within a population is a basic but important step for understanding the roles of parasites in natural systems. Among intraspecific studies on vertebrate hosts and metazoan parasites, host body size (length/mass) is probably the most frequently reported factor determining parasite infection levels (intensity/abundance), where positive relationships are usually observed. However, whether the positive correlations between host size and infections represent a general rule remains unclear, as do the factors determining the strength of these correlations. Here, by conducting meta-analyses using 793 infection-versus-body size correlations compiled from 153 publications, we tested whether the positive relationship between host body size and parasite infections represents a general pattern across all vertebrate host taxa and major metazoan parasite groups. Results showed that overall correlations were significantly positive but relatively weak (Zr = 0.206), indicating that the presumed positive relationships between host body size and infections are not strongly supported as a general rule, and that the strength of correlations varied greatly among host-parasite systems. We also found that studies on mammals and birds were more likely to report non-significant correlations, possibly due to behavioral, developmental, and physiological characteristics, compared with those on fish. Moreover, effect sizes varied depending on study methods, such as infection or host body size measures used, suggesting that not only biological processes but also statistical noise associated with these methods influence the relationships. Our study provides the first quantitative evidence showing that positive relationships between host body size and infection are not a universal pattern and are relatively heterogeneous among host-parasite systems. Based on these findings, we stress the importance of testing rather than assuming host size-infection relationships in any given host-parasite system, and considering both biological and other underlying processes, to better understand the determinants of infection in nature.

Parasites undoubtedly comprise a large proportion of biodiversity and biomass in living organisms and play ecologically and evolutionarily significant roles (Lafferty et al. 2006, Kuris et al. 2008, Dobson et al. 2008, Carlson and Dallas 2020). For instance, although parasites are usually small and cryptic, they strongly modify host population dynamics (Hudson et al. 1998, Anderson and May 1979), species interactions (Hudson and Greenman 1998, Mouritsen and Poulin 2005, Hatcher et al. 2006), community structure and food-web dynamics (Dunne et al. 2013, Klemme et al. 2024), and ecosystem functioning (Wood et al. 2007, Sato et al. 2012, Brian et al. 2022). Parasite infections act as major evolutionary drivers of host ecological and physiological traits (Sheldon and Verhulst 1996, Marcogliese 2004). Therefore, elucidating the determinants of parasite infection levels among host individuals, such as parasite abundance, is a crucial topic in light of its significance in ecology and evolution. At global and regional scales, parasite infection levels are affected by many factors such as climatic factors (e.g. temperature or precipitation rate: Ostfeld et al. 2005, Martins and Poulin 2024) and host-related factors (host density or diversity: Anderson and May 1979, Arneberg et al. 1998, Kamiya et al. 2014). Likewise, at the host individual scale, numerous factors such as host morphological, behavioral, and physiological traits generate variation in parasite infection levels (Knudsen et al. 2004, Blanchet et al. 2009). Among these factors, the most frequently reported determinant of infection levels in vertebrate hosts is probably host body size (i.e. host body length/mass), with many studies usually reporting positive relationships between infection levels and host body size (Poulin 2000). Many possible mechanisms can produce this positive relationship. For instance, bigger hosts generally have larger surface areas, and hence infective stages of parasites can more easily find and attach to them (Poulin and Rohde 1997, Henriksen et al. 2022). Not only do larger surface areas matter, but also the greater internal space within larger hosts allows them to harbor more parasite individuals (Poulin 2000, Poulin and Morand 2004). Larger hosts are generally older and have been exposed to parasite infection for a longer time, resulting in greater accumulation of parasites over the course of their lifetime (Zelmer and Arai 1998). Because body size positively correlates with metabolic demands (Brown et al. 1995), larger hosts show higher feeding rates, resulting in higher ingestion rates of trophically transmitted parasites (Poulin and Morand 2004). Additionally, while larger hosts may tolerate heavy infections with numerous parasites, smaller hosts may not and are likely to die from infections (Cardon et al. 2011, Marino et al. 2016). This parasite-induced host mortality also contributes to the observed positive correlation between host size and parasite infection levels by removing any small-bodied hosts infected by many parasites. Moreover, larger hosts are generally dominant in social hierarchies, which may lead to increase interactions with other individuals and better access to preferred positions (Nakano 1995, Schmid-Hempel 2017). These factors collectively increase the likelihood of parasite encounters (Habig and Archie 2015, Schmid-Hempel 2017). Overall, these ecological mechanisms can interactively generate the positive intraspecific relationship between host size and infection levels. Despite the overall presumed general positive relationships between vertebrate host size and parasite infections, surprisingly, only one study has explored the generality of this rule (Poulin 2000). However, this study focused solely on fish–parasite studies (Poulin 2000), thus general patterns across all vertebrate taxa are still not known. Moreover, it is noteworthy that this earlier study found that the strength and direction of correlations varied considerably, and the overall mean effect size (i.e. correlation coefficients corrected for host sample size) was not significant (Poulin 2000). This suggests that various factors, such as parasite taxonomic group or transmission mode, may influence size-related infections, and presumed positive relationships may not be universally present. Indeed, among other vertebrate groups, studies reporting negative or neutral relationships in host-parasite systems do exist (e.g. Monteiro et al. 2011, Soares et al. 2014), although positive relationships remain predominant. Therefore, whether the positive correlation between host body size and parasite infection levels represents a general pattern remains unsolved and questionable. Perhaps no universal rule governs the relationship between these two factors. In this study, we explored the generality of the intraspecific relationship between host body size and parasite infection levels across all vertebrate host taxa and metazoan parasite groups through a systematic review and meta-analysis. We specifically formulated several hypotheses regarding these relationships. First, we hypothesized that overall correlations would be positive but vary among host taxonomic groups. For instance, we expected many fish host-parasite systems to show positive relationships between host size and infections, as reported previously (Poulin 2000), whereas mammals and birds would not exhibit such clear patterns, leading to weaker overall correlations than those observed in fish. This is because the latter two groups have sophisticated developmental immune systems (e.g. (Boehm 2012, Riera Romo et al. 2016) or parasite avoidance/removal behaviors (Hart 1992, Bush and Clayton 2018), which are likely to strengthen with age and experience, i.e. with body size (Villa et al. 2016). Thus, even if larger hosts are more likely to acquire infections due to their greater surface areas or longer exposure times, larger/older bird and mammal individuals may be able to remove infections through physiological and behavioral mechanisms, possibly masking any relationship between host size and infections. Second, we hypothesized that the strength and direction of correlations would vary among parasite taxa. Each parasite taxon exhibits different ecological characteristics, such as transmission modes, attachment sites, infection duration, and virulence (Poulin 2011). All these biological traits may influence the relationship between host size and parasite infections. Although one previous study focusing on fish host-parasite systems did not find clear differences among parasite groups (Poulin 2000), that study only analyzed a limited number of effect sizes ( N = 58), primarily from taxonomically biased parasite groups due to its focus on fish hosts. Therefore, larger datasets that include a greater diversity of taxa will highlight whether differences exist among parasite taxonomic groups. Third, we predicted that the choice of infection measures (intensity or abundance) may influence whether or not relationships are found, and how strong they appear. When examining the relationships between host size and parasite infections, intensity (the number of parasites per infected host) and abundance (the number of parasites per host, including uninfected individuals) are the two main infection measures frequently used. In general, many parasites exhibit an aggregated distribution, where most individuals harbor no parasites, while a small proportion carry large numbers of parasites (Shaw and Dobson 1995). Due to this nearly universal pattern, including uninfected individuals with zero parasites might introduce high variance in host size, potentially obscuring the relationship between host size and infections compared to analyses using only infected hosts, i.e. intensity. Indeed, a previous meta-analysis focused on fish body condition indices and parasite infection levels (i.e. abundance, intensity, prevalence) revealed that the inclusion or exclusion of uninfected hosts affected the overall mean effect sizes, suggesting that high variance in body condition among uninfected fish obscured the relationship and its detectability (Hasegawa and Poulin 2025). Although Poulin (2000) also hypothesized that the inclusion or exclusion of uninfected fish could influence the strength of the correlation between host size and parasite infections, this prior fish-focused study did not find any significant effect. We systematically and quantitatively reviewed 793 relationships between host size and parasite infection levels, compiled from 153 publications, covering a wide range of vertebrate hosts and metazoan parasite systems. By analyzing this large dataset across diverse host-parasite systems, we found that the commonly presumed and frequently reported positive relationship between host size and parasite infection is not a strongly supported universal pattern across all taxa. Additionally, our analysis identified several key factors that influence the strength and direction of this relationship, shedding light on the complexity of host-parasite interactions.

Literature search & Data extraction To retrieve studies examining vertebrate host size –parasite infection level relationships, we searched the ISI Web of Science (using the “topic” option) on September 25, 2024. The following keyword string was used: (”fish*” OR ”mammal*” OR ”bird*” OR ”reptile*” OR ”amphibia*” OR ”vertebrate*”) AND (”macroparasit*” OR ”ectoparasit*” OR ”endoparasit*” OR ”endohelminth*” OR ”helminth*” OR ”digenea*” OR ”trematod*” OR ”nematod*” OR ”cestod*” OR ”tapeworm*” OR ”acanthocephala*” OR ”monogenea*” OR ”glochid*” OR ”copepod*” OR ”tick*” OR ”flea*” OR ”mite*”) AND (”body length*” OR “body size*” OR “body weight*” OR “body mass*” OR ”fork length” OR ”standard length” OR ”total length” OR ”host size*” OR ”snout-vent length*” OR “snout-urostyle length*”) AND (“intensit*” OR ”abundance*” OR ”load*” OR ”number*” OR ”burden*” OR ”infection level*”). A total of 1,597 publications were retrieved from the above search, of which 699 were retained after the titles, abstracts and keywords were screened for relevance (Fig. A1). We then reviewed the full text of the remaining 699 publications and retained the 153 that satisfied the following criteria: (1) publications focusing on macro-parasites infecting vertebrate hosts (excluding micro-parasites such as protozoa and viruses, and non-vertebrate hosts), (2) publications reporting correlation coefficient ( r ) or coefficient of determination ( r 2 ) for relationships between host length/weight – the number of parasites (mainly intensity and/or abundance) at the host individual level (not the host population level); (3) publications using host length and/or mass as host body size measures (excluding studies using length/mass of specific body parts such as tarsus length, spleen mass, or head length); (4) publications written in English and published in peer-reviewed journals. Reviews (including meta-analyses), conference proceedings and technical reports that might not have been peer-reviewed were excluded. From these 153 publications, we extracted data for each reported vertebrate host size –parasite infection relationship. When a publication reported numerous host size – infection relationships, we extracted the following data separately and recorded them as separate entries in the dataset. As a result, our dataset included 793 host size – infection relationships (Fig. A1). Specifically, the following information was recorded in each case. Parasite species and taxonomic group: the higher taxonomic levels (genus, family, order, class, phylum) for each parasite species were recorded based on information from the Catalogue of Life (www.catalogueoflife.org). When information was unavailable for the focal parasite species, we obtained taxonomic details from the source or other relevant publications, or from other databases such as WoRMS (https://www.marinespecies. org). Parasite group: based on the taxonomic categories described above, we grouped the parasites into the following parasite categories for statistical analyses: Acanthocephalan, Cestode, Copepod, Monogenean, Nematode, Trematode metacercaria, Trematode adult, Terrestrial arthropod, Numerous species, and Other parasites. Due to their differing ecological characteristics (e.g. transmission modes, attachment sites, potential host types), “Trematode” was divided into “trematode metacercaria” and “trematode adult”. Data on ticks ( N = 10), mites ( N = 4), lice ( N = 1), and parasitic flies ( N = 1) were combined as “Terrestrial arthropod” because of their small sample sizes and ecological similarity. Other parasite groups with small sample sizes (Isopod, N = 8; Branchiuran, N = 7; Freshwater mussel glochidium, N = 1; Trematode of all stages, N = 2) were combined as “Other parasites”. Some studies investigated the relationship between host size and infection levels by pooling all detected parasite species together, regardless of their taxon. These were assigned to the “Numerous species” category. Moreover, some studies pooled several species of parasites belonging to the same higher taxon in a single analysis (i.e. Acanthocephalan, Cestode, Copepod, Monogenean, Nematode, Trematode metacercaria, Trematode adult). These host size-infection relationships were assigned to the relevant taxonomic categories above due to the shared ecological characteristics of related parasites. Host species and taxonomic group: similar to parasite species, we also recorded the higher taxonomic levels of the hosts (genus, family, order). Based on these taxonomic categories, we classified each host into one of these five vertebrate groups: mammal, bird, reptile, amphibian, and fish. Host sample size: we recorded the number of hosts used to calculate the correlation coefficients ( r ) or the coefficients of determination ( r 2 ) for the host body size-infection relationships. In the meta-regressions described below, we excluded relationships based on extremely small sample sizes (i.e. N < 20). Host body size measures: host body size measures used in each study were recorded. However, different body size measures were generally used across vertebrate host taxa. For instance, standard length (from the tip of the snout to the posterior opening of the cloacal slit) and fork length (from the tip of the snout to the most posterior end of the middle caudal ray) were used only in fish, while snout-vent length (from the tip of the snout to the posterior end of the anus) were used only in amphibians and reptiles. Therefore, all body size measures were largely categorized as either “body length” or “body mass” for the analysis. Subcategories are provided in the Supplementary file 1. Host body size range: we also recorded the maximum and minimum values of host body size, when available, because the size range can influence the detectability of host size-infection relationships (Poulin 2000). Furthermore, to standardize the body size range across data points for analysis (see below), we calculated relative body size range (RBS) as follows; (maximum body size - minimum body size) / (maximum body size + minimum body size). Infection measure: following the definitions in Bush et al. (1997), we recorded the infection measures used in each study as follows: intensity (the number of parasites per infected host) or abundance (the number of parasites per host, including uninfected ones). Other infection measures, such as parasite density (the number of parasites per unit host mass) and parasite mass (the total mass of parasite individuals within a host), were rarely used and were thus grouped as “Other infection measures”. Study design: we assigned each study to one of the following categories: (1) field studies in which hosts were captured in natural environments, (2) experimental studies in which hosts were experimentally infected under controlled conditions, and (3) domestic studies in which hosts were obtained from domesticated environments such as aquaculture facilities (e.g. fish farms or marine cages) and zoos. Correlation coefficients ( r ): correlation coefficients (e.g. Pearson’s correlation coefficient r, Spearman’s correlation coefficient r s ) that quantified the relationship between host body size and parasite infection were recorded. When a study reported the coefficient of determination ( r 2 ), we converted it into a correlation coefficient. However, we excluded data points where only r 2 was reported without information on the direction (positive or negative) of the correlation. Publication ID and publication year: we assigned a unique ID to each publication because most publications reported multiple host body size-infection relationships, and this non-independence was considered in the analyses described below. We also recorded the year of publication. Overall, 793 host body size–infection relationships were compiled from 153 publications (Fig. A1). Of these, 692 host body size–infection relationships from 144 publications included correlation coefficients ( r ) or coefficients of determination ( r 2 ) with directionality, calculated from sufficient host sample sizes (i.e. N > 20), along with all other required data (Fig. A1). These host body size–infection relationships were termed the “full dataset” and were used for meta-regressions. Additionally, subsets of this dataset reported host body size ranges ( N = 244 from 48 publications, 35.3% of the 692 relationships), which allowed us to calculate RBS (Fig. A1). These datasets, termed as “RBS dataset”, were used for other meta-regressions (see below, Fig. A1). Finally, as our datasets was highly biased toward fish hosts ( N = 535 from 114 publications, 77.3% of the 692 relationships; Table 1, Fig. A1), we further constructed meta-regression models focusing only on this “fish dataset”. All statistical analyses were performed in R v. 4.1.1. (R core team 2024). Construction of the meta-regression models and associated effect size calculation were conducted using the package “ metafor ” v. 4.8.0 (Viechtbauer 2010). Before model construction, we transformed raw correlation coefficients into Fisher’s z -transformed correlation coefficients, Zr, as an effect size using the function “ escalc ” in the “ metafor ” package. Meta-regressions using the full dataset Focusing on the full dataset (i.e. 692 body size-infection relationships from 144 publications), we constructed several meta-regression models. First, we constructed an intercept-only mixed-effects model (MEM) with a restricted maximum likelihood (REML) estimator using the “ rma ” function, where we did not include any moderator to examine the overall mean effect sizes ( Zr ) across host body size-infection relationships. This model also estimated I 2 , an indicator of heterogeneity among relationships (Nakagawa and Santos 2012). Second, we constructed another MEM, where we only included “publication year” as a moderator to examine potential temporal effects (i.e. whether published effect sizes increase or decrease over time; Costello and Fox 2022). In this model, we used the “ rma ” function with REML estimator, as described above. Third, we constructed an MEM using REML with the “ rma.mv ” function, where we included all moderators to explore the specific drivers of the relationships. We included the following moderators: (1) body size measure (two levels: body length, body mass), (2) parasite group (ten levels: Acanthocephalan, Cestode, Copepod, Monogenean, Nematode, Trematode metacercaria, Trematode adult, Terrestrial arthropod, Numerous species, and Other parasites), (3) host taxon (five levels: mammal, bird, reptile, amphibian, fish), (4) infection measure (three levels: abundance, intensity, other infection measures), and (5) study design (three levels: field, experimental, and domestic studies). To account for any phylogenetic effects, we included the “parasite phylum” and “host family” as random effects. Additionally, since most studies contributed multiple correlation coefficients, we also included “publication ID” as a random effect. For the first and third models, potential publication biases were visually evaluated using funnel plots. Meta-regressions using the RBS dataset As indicated by a previous study, the strength of host body size-infection relationships can be influenced by the range of host body sizes (Poulin 2000). Therefore, we constructed models using the RBS dataset (Fig. A1), for which host body size range was reported (i.e. 244 body size-infection relationships from 48 publications). As with the models described above, we first constructed an intercept-only MEM to examine the overall correlation coefficients and I 2 . Second, we constructed a MEM that included RBS (see above for calculation) as a moderator, along with all other moderators and the random effects described above. However, we did not include “host taxon” in this model because this dataset mainly consisted of studies using fish and amphibian hosts (59.0% and 30.3%, respectively). We also excluded “study design” as a moderator, as nearly all data were derived from field studies (99.2%). Meta-regressions using the fish dataset We constructed several models using the fish dataset (i.e. 535 body size-infection relationships from 114 publications; Fig. A1). As described above, we first constructed an intercept-only MEM to explore the overall correlation patterns. We then constructed MEM including moderators. In this MEM, we used the same moderators (i.e. parasite group, infection measure, body size measure, and study design) and random effects (i.e. parasite phylum, host family, and publication ID) as described above. To increase the sample size, we excluded RBS as a moderator.

Results overview In total, we retrieved 793 host body size-infection relationships compiled from 153 publications (Fig. A1). The number of host and parasite groups represented in the dataset is summarized in Table 1. Overall, 77% of the relationships involved fish hosts, whereas data from other vertebrate taxa were relatively scarce (Table 1). Nematodes were the most frequently reported parasite group, followed by Monogenean, Trematode adult, and Trematode metacercaria (Table 1). Studies using parasite abundance as the infection measure were the most common ( N = 580, 73.4%), followed by those using infection intensity ( N = 187, 23.6%) and other infection measures ( N = 26, 3.3%). Similarly, most studies used body length as the body size measure ( N = 582, 73.4%), whereas those using body mass were relatively few ( N = 211, 26.6%). Finally, field studies were predominant in the dataset ( N = 724, 91.3%), followed by experimental studies ( N = 52, 6.6%) and domestic studies ( N = 17, 2.1%). The dataset is available as a Supplemental file 1. Meta-regressions using the full dataset There appeared to be no publication bias based on a visual inspection of the funnel plots, as the data were largely distributed symmetrically (Fig. A2). The intercept-only MEM showed that heterogeneity among studies was very high ( I 2 = 96.05%; Fig. 1). As expected, the overall effect size (i.e. Fisher’s Zr ) of the body size-infection relationships was positive (mean Zr = 0.206 [95% CI = 0.172 to 0.240], SE = 0.017, P < 0.0001; Fig. 1). A MEM including publication year as a moderator revealed a slight decline in effect sizes over time, although this trend was not statistically significant (Estimate = −0.006 [95% CI = −0.014 to 0.002] , SE = 0.004, P = 0.135 ; Fig. A3). In the MEM including all moderators, we found varied effect sizes among host groups (Fig. 2). Fish and reptiles were the only groups showing significant positive correlations between body size and parasite infection, whereas other groups exhibited no significant correlations (Fig. 2; Table A1a). All parasite groups showed significant positive correlations (Fig. 3; Table A1b). Both studies using parasite abundance and those using infection intensity reported significant positive correlations (parasite abundance: r = 0.285 [95% CI = 0.208 to 0.363]; parasite intensity: r = 0.250 [95% CI = 0.168 to 0.331] ), whereas studies using other infection measures showed no correlations ( r = 0.082 [95% CI = −0.030 to 0.193] ). Similarly, both body size measures, body length and body mass, showed positive correlations (Body length: r = 0.27 [95% CI = 0.187 to 0.342]; Body mass: r = 0.30 [95% CI = 0.218 to 0.377] ). Domestic studies reported non-significant correlations, while both field and experimental studies showed significant positive correlations (Fig. 4; Table A1c). Meta-regressions using the RBS dataset When RBS was included in the analysis, the overall correlations between body size and infection became weaker, but remained significantly positive ( mean Zr = 0.109 [95% CI = 0.048 to 0.170], SE = 0.031, P = 0.0004 ). For different subsets of correlations, however, the inclusion of RBS caused many to lose their significance. Thus, among all parasite groups, copepods were the only group that still showed a significant positive correlation (Fig. A4a). With respect to the infection or host size measures used, studies using infection intensity and body mass showed non-significant correlations (Fig. A4b, c). Meta-regressions using the fish dataset When focusing on the fish dataset, the overall correlations between host body size and infection were significantly positive ( mean Zr = 0.230 [95% CI = 0.190 to 0.271], SE = 0.021, P < 0.0001 ). All examined parasite groups showed significantly positive correlation coefficients (Fig. A5a). While studies using parasite abundance and intensity reported significant positive correlations, those using other infection measures were not significant (Fig. A5b). Both studies using body length and body mass as measures of size showed significant positive relationships (Fig. A5c). However, domestic studies on fish hosts tended to report non-significant relationships (Fig. A5d).

Given the critical roles of parasites in ecosystems (Lafferty et al. 2006, Dobson et al. 2008, Kuris et al. 2008, Carlson et al. 2020), elucidating the determinants of parasite infection levels is a fundamentally important issue in ecology and evolutionary biology. Intraspecific variation in host body size has frequently been reported as a key driver explaining large variations in metazoan parasite infection levels, where most studies assume and expect a positive relationship between host body size and parasite infection (Poulin 2000). However, surprisingly, no study has explored whether this pattern holds consistently across vertebrate taxa. Here, by analyzing 793 body size-metazoan parasite infection relationships compiled from 153 publications across all vertebrate groups, we explored the generality of the relationship between host body size and infection, as well as its potential drivers. Our major findings are (1) overall correlations between host body size and infection levels were significantly positive but relatively weak ( Zr = 0.21), and this relationship became even weaker when host body size range was included, though it still remained significant ( Zr = 0.11); (2) effect sizes varied among host taxa, with no significant positive correlations detected in mammals, birds, and amphibians, partially supporting our prediction; (3) no clear differences in effect sizes were found among parasite groups; (4) the choice of infection measure (e.g. intensity, abundance) and study design (e.g. field studies, domestic studies) influenced the results, but these effects were observed only when host body size range was considered or when analyses were focused on fish only. Overall, although a positive association between host body size and parasite infection is widely assumed, our findings suggest this relationship is not universal and varies considerably among host–parasite systems. As predicted, we found an overall non-significant positive correlation in mammals and birds, while clear positive overall correlations were observed in most other groups, particularly in fish hosts. This pattern may be explained by the more sophisticated physiological and behavioral resistance strategies exhibited by mammals and birds (Hart 1992, Riera Romo et al. 2016). In general, mammals and birds possess adaptive immune systems that develop and strengthen over the course of their lives. As a result, older (typically larger) individuals are more capable of effectively clearing parasite infections. Although immune function tends to be weakest during early and late life stages (Miller 1996), a positive correlation between immune competence and host age (or size) is generally maintained. Additionally, many species in these taxa exhibit behavioral defenses such as avoidance of infected conspecifics, grooming, and preening (Hart 2011, Bush and Clayton 2018). Like immune function, these behaviors are often more developed in older (again, typically larger individuals) (Villa et al. 2016), further enhancing their resistance to parasites. Taken together, the ability of larger or older mammals and birds to reduce parasite burdens through both physiological and behavioral strategies may obscure or weaken the expected positive correlations between host size and infection levels. Another possible reason why we did not detect clear patterns in mammals and birds is the difference in their growth patterns compared to other vertebrate groups and its resultant statistical consequences. While many mammals and birds show determinate growth, in which growth ceases at sexual maturity (Sebens 1987), other groups, particularly most fish, exhibit indeterminate growth, continuing to grow even after reaching sexual maturity (Sebens 1987). As a result of these contrasting growth patterns, the range of body sizes used in published studies tends to be narrower in mammals and birds, which may limit the detectability of positive correlations between body size and parasite infection. In contrast, host groups with indeterminate growth, especially fish, often display a broader range of body sizes, which facilitates the detection of such positive correlations. Despite initial predictions, no clear patterns were found among parasite taxa, and overall correlations were positive across all groups. This pattern also held true when we focused on fish hosts only. Poulin (2000) reported similar results, showing that most parasite groups had positive correlations with host body size, but no clear patterns emerged regarding their transmission strategies (i.e. trophic transmission or direct skin contact). These results indicate that intraspecific host body size-infection relationships are more complex and cannot be explained solely by parasite ecological traits, such as transmission modes or attachment sites, even though positive correlations are common. Variation in virulence (pathogenicity) among parasites may be one factor that determines host body size-infection relationships. Heavily infected hosts or infected hosts with smaller body sizes are often missing from datasets due to infection-induced mortality (Crofton 1971, Adjei et al. 1986), which can obscure positive correlations between host size and infection (Poulin 2000). This trend may be particularly clear when the parasites have high virulence. Even within the same taxonomic groups or species, each parasite species or population shows different levels of pathogenicity (Ebert 1994, Kalbe et al. 2016), which can be shaped by various factors such as co-evolutionary processes with their hosts (Ebert 1994, Kalbe et al. 2016). Therefore, variation in virulence among parasite species and populations can lead to differences in the removal rates of heavily infected or smaller infected individuals from host populations, potentially contributing to variation in the strength of positive correlations. Another possible explanation is that different regulatory factors may operate in parasite populations across study systems. For instance, density-dependent regulatory mechanisms, such as intra- or interspecific competition among parasites, can play an important role (Shostak and Scott 1993). As our results show, larger hosts generally harbor more parasite individuals. They also tend to host a greater number of parasite species (Kamiya et al. 2014, reviewed by Poulin and Morand 2004). These coinfecting conspecific or heterospecific parasites directly compete for resources such as space (Cox 2001, Budischak et al. 2018), or indirectly affect each other through host immunity responses or host behavioral changes (Brian 2025, Ezenwa et al. 2010), thereby regulating each other’s populations. Therefore, even when a parasite species infects larger hosts, its abundance may not increase to maximum levels due to such regulatory constraints, which could mask positive relationships with host size. This latter explanation may account for the MEM results that included host body size range, where only copepods and trematode metacercariae showed positive correlations. Since these two parasite groups typically infect external surfaces and occur at relatively low intensities (Rohde 1991), regulatory effects may be less pronounced compared to other parasite groups (Rohde 1991), although further studies are required to support this explanation. Studies conducted in domestic environments were more likely to report non-significant relationships, although we should note that all data from domestic environments were based on fish hosts. This may stem from several mechanisms. First, even smaller individuals may exhibit higher infection levels in domestic environments due to extremely high host densities, which facilitate parasite transmission. Second, variation in body size among host individuals tends to be smaller in domestic environments than in the field because of standardized conditions (e.g. constant food supply and water temperature), which may obscure positive relationships. In either case, this result provides an important insight into studies examining host size-parasite infection relationships: those studies conducted under domestic environments do not necessarily reflect true relationships between host size and parasite infections. There were no clear differences in effect sizes between studies using intensity (excluding uninfected hosts) and using abundance (including uninfected hosts) as measures of infection, but effect sizes in studies using intensity became non-significant when host body size range was included as a moderator. Many parasite species show an aggregated distribution, in which most hosts harbor none or a few parasites, while heavily infected hosts are rare within a population (Shaw and Dobson 1995). Studies using intensity exclude these uninfected hosts, which constitute a large proportion of the host population. Thus, the removal of uninfected individuals may reduce statistical power and fail to capture true relationships between host size and parasite infection. Therefore, one recommendation based on this result is to test the relationship using both measures when available, as the inclusion or exclusion of uninfected individuals may influence the results. When host body size range was included, the host size versus infection levels relationship in studies using body mass also became non-significant. This may be due to the greater variance commonly observed in body mass compared to body length. Body mass can vary temporally, as it reflects recent host foraging activity (Cone 1989). Not only foraging activity but also other physiological conditions, such as lipid and water content, can influence body mass (e.g. Kaufman et al. 2007), all of which contribute to high variance in body mass, but not in length. Based on these results, it may be preferable to use body length, rather than body mass, when examining the relationship between host size and parasite infection, as length is a better proxy for age.

For the first time, we provide firm evidence showing that the widely assumed positive correlation between host body size and parasite infection is not a ubiquitous pattern across all vertebrate hosts and metazoan parasites. We also successfully identified several key drivers of this relationship. Based on these findings, we offer several important implications for future studies. First, body size-infection relationships should be carefully examined in each host-parasite system. It has been widely assumed that body size is one of the major predictors of parasite infection levels and species richness (Kamiya et al. 2014, reviewed by Poulin and Morand 2004), and many epidemiological models also consider host body size (or age) as a main driver of infection dynamics (Banerjee et al. 2017, Downie et al. 2021), often assuming positive relationships between host size and infection level. Despite these previous expectations, we again found that positive relationship between host size and infection is not a universal pattern, although such relationships are commonly observed. Therefore, to better predict realistic infection levels and their dynamics, such relationships should be carefully explored in any focal host-parasite system. Second, the methods used should be carefully considered when examining the relationship between host size and infection. We identified that choices of infection measures (intensity, abundance), body size measures (body length, body mass), and study designs (domestic, experiments, field studies) can affect the detectability of the true relationship between host size and infection. These factors do not always affect the results, but they can significantly influence the relationships, especially when the range of host body size or the sample size is small. Indeed, previous studies have found inconsistent patterns even among similar study systems (i.e. the same species but different populations or regions; e.g. White et al. 2020), which may suggest that statistical fluctuations were induced by differences in study methods. In summary, regardless of the direction of the relationship, we identified and discussed possible underlying mechanisms that may differ among study systems. Further empirical studies are encouraged to elucidate the specific processes driving the link between host size and parasite infection.

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Forest plot showing the 95% confidence interval (CI) of effect sizes between host body size and parasite infection for each study considered in the present paper, ranked from most negative (top) to most positive (bottom). The mean effect size and its 95% CI are represented by a blue dot and thick bar. Figure 2. Orchard plot showing the effect sizes for each vertebrate host group estimated from a mixed-effects model (MEM) using the full dataset (see main text). Each point represents a different host body size-infection relationship. The mean effect size and its 95% confidence interval (CI) are shown. The size of each plot indicates the relative host sample size used for each original analysis. Figure 3. Orchard plot showing the effect sizes for each parasite group estimated from a mixed-effects model (MEM) using the full dataset (see main text). Each point represents a different host body size-infection relationship. The mean effect size and its 95% confidence interval (CI) are shown. The size of each plot indicates the relative host sample size used for each original analysis. Figure 4. Orchard plot showing the effect sizes for each study design estimated from a mixed-effects model (MEM) using the full dataset (see main text). Each point represents a different host body size-infection relationship. The mean effect size and its 95% confidence interval (CI) are shown. The size of each plot indicates the relative host sample size used for each original analysis. Information & Authors Information Version history Copyright This work is licensed under a Non Exclusive No Reuse License.

Authors Metrics & Citations Metrics Article Usage 460views 180downloads Citations Download citation Ryota Hasegawa, Daniela de Angeli Dutra, Bronwen Presswell, et al. Does bigger mean sicker? A systematic review and meta-analysis of the intraspecific relationship between host body size and parasite infection across vertebrate taxa. Authorea. 07 July 2025. DOI: https://doi.org/10.22541/au.175188251.12575185/v1 DOI: https://doi.org/10.22541/au.175188251.12575185/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu.