A review of determinants for dairy farmer decision making on manure management strategies in high-income countries

In manure collection stage, the manure is transferred to either storage or land application. The use of different manure collection systems is likely driven by a set of factors including both farm infrastructure as well as farmer priorities and goals. Importantly, manure collection systems appear to be significantly related to farm size (Powell et al 2005, Sheppard et al 2011) and go on to influence manure storage and application strategies. As noted previously, evidence suggests that small and medium-sized farms are more likely to collect solid manure while larger facilities are more likely to collect manure in slurry or liquid forms (Filson et al 2003, Sheppard et al 2011, Aguirre-Villegas and Larson 2017). The literature indicates that scrape and flush systems are the most common means of collecting slurry and liquid manures (Dou et al 2001, Meyer et al 2011, Aguirre-Villegas and Larson 2017). Bedded pack and gutter cleaners and other scrape systems were the most common collection methods mentioned for solid manure systems (Dou et al 2001, Filson et al 2003, Meyer et al 2011, Sheppard et al 2011, Aguirre-Villegas and Larson 2017).

A recent study from dairy farms in Wisconsin finds that 70% of the small and medium farms used solid manure collection, while large facilities were more likely to employ slurry or liquid systems. These different collection and handling systems were correlated with the housing systems most common at small to medium and large scales (Aguirre-Villegas and Larson 2017). Manure collection was found to be more frequent among lactating cows and less frequent among dry cows and heifers, which could also be related to different housing systems for each type of animal (Dou et al 2001).

In Pennsylvania, farms collecting solid manure mainly did so via bedded pack, while 84% of farms collecting slurry, semisolid or liquid manure employed scrape collection techniques (Dou et al 2001). However, in California, larger farms also used manure as bedding, but did so following collection of corral scrapings and/or processing to separate out solids and liquids (Meyer et al 2011). This contradiction exemplifies a theme in the literature; namely, that there can be substantial variability in manure collection methods across farm size and regions (Powell et al 2005, Sheppard et al 2011).

Evidence indicates that manure storage is often a function of farm size and is related to the selection of other MMS. Existing data from Wisconsin indicate that large and medium farms are more likely to have long-term storage and treatment infrastructure than smaller farms (Aguirre-Villegas and Larson 2017). Another study examining Wisconsin dairy farms found that many small- to medium-sized operations employ pasture-based feeding systems, which do not require manure collection or storage and, consequently, avoid the time, labor and infrastructure costs associated with the storage and treatment systems necessary in confined feeding operations. Organic pasture-based dairy farms, however, were more likely to store manure in lined structures or piles than were larger confinement operations (Brock and Barham 2009). This could indicate that restrictions on chemical fertilizers might motivate more efficient use of manure nutrients and highlights the potential connection between farm-wide management systems and manure storage strategies (Brock and Barham 2009). An earlier study in Pennsylvania correlated specific manure storage strategies with either dry (non-milk producing due to age or seasonal reproductive cycles) or lactating cows, highlighting the interconnectivity of manure storage and other farm-level factors such as breeding and housing systems. At that time (2001), there were few instances of alternative manure collection and storage systems, such as methane digesters or treatment lagoons, and in fact 30% of farmers reported no manure storage system at all (Dou et al 2001). In contrast, a study from the late 1990s in Ontario found that the majority of farmers stored manure in an outdoor pile, while the largest farms reported using liquid systems with storage lagoons (Filson et al 2003). In a survey of Louisiana dairy farmers, management of wastewater and runoff from cow housing facilities had the highest rate of adoption amongst a suite of BMPs related to manure storage (Rahelizatovo and Gillespie 2004a). Glenk et al found that covering stored manure, using anaerobic digesters and removing manure frequently as GHG mitigation strategies, were less frequently adopted compared with other GHG mitigation strategies in Scotland (Glenk et al 2014). Later findings from Canada suggest farms typically stored slurry between 1 month and 1 year, with 97% not agitating manure, and only 10% of farms separating liquids and solids (Sheppard et al 2011).

Many studies found that there is significant potential for adoption of more environmentally sound manure processing strategies. In Europe, manure solid–liquid separation and anaerobic digesters have the greatest adoption potential (Hou et al 2016). In New York, more than half of farmer respondents expressed some or great interest in a community-level manure digester (Swindal et al 2010). Another study of New York dairy farmers found that interest in anaerobic digester technology is not inherently scale-based, and that the impact of farm size on interest is mediated by other farm-scale variables, such as reliance on pasture or interest in biotechnology (Welsh et al 2010). More recently, Strazzera et al found that 77% of dairy farmers in an agricultural region of Sardinia, Italy were interested in the potential for biogas/anaerobic digesters at their farms (Strazzera and Statzu 2016). However, in England the potential adoption rates were much lower in one survey, where only 9% of farmers indicated they would consider investing in a digester; 30% responded maybe and 60% indicated they would not consider investing (Tranter et al 2011). Similarly, a Pennsylvania study found that only 8 out of 944 farms used manure processing strategies such as methane digesters or treatment lagoons. In Wisconsin, only 7 out of 143 farms processed manure via anaerobic digester (Aguirre-Villegas and Larson 2017). Heterogenous findings are reaffirmed by a study across four regions of Australia, which found high variability of adoption of biogas technology across the different regions (Wirth et al 2013).

Aside from digester technology, another manure processing technique discussed widely in the literature is solid–liquid separation. Meyer et al concluded that dairy farms in California's Central Valley increased the use of solid–liquid separation from 54% in 1994 to up to 70% in 2007 (Meyer et al 2011). However, in Wisconsin, less than 17% of farms utilized manure separation technology, via either solid–liquid separation or sand separation (Aguirre-Villegas and Larson 2017). In the Netherlands, one study found that farmer attitude and the compatibility of current manure application technologies were significant factors influencing farmers likelihood of adopting manure separation technologies (Gebrezgabher et al 2015).

Application of manures is connected with how manure is stored and is often related to farm size as well. Larger Wisconsin dairy farms typically land applied seasonally in spring and fall and used multiple application techniques as compared to smaller farms, which applied weekly or even daily due to a lack of longer-term storage structures (Aguirre-Villegas and Larson 2017). Early evidence from Pennsylvania in 2001 found that most manure application was done by surface spreading (95%), and incorporation was not practiced by most farms (Dou et al 2001). In the Netherlands, shallow manure injection was common among farmers surveyed (56% of farms), while 22% used trailing shoe injector and 12% used drag bars (Gebrezgabher et al 2015). In Canada, however, one study found that most slurry manure was broadcast and not injected at the time farmers were surveyed (Sheppard et al 2011).

In summary, various farm-level factors—including farm size, feeding system, housing system, and breeding system—were identified as influencing adoption of specific manure collection, storage and treatment systems. There was an indication that management decisions around the storage and treatment of manure may offer the greatest opportunity to reduce GHG emissions associated with dairying. However, farmer interest in adopting new storage and treatment technologies varied. Certain manure processing strategies and treatment methods, such as anaerobic digesters and solid–liquid separation, were more common and were generally adopted by larger farms that also applied manure less frequently than smaller farms thanks to their greater long-term storage capacity. The literature presents consistent evidence indicating that substantial heterogeneity exists across farm sizes and geographic locations regarding the most common methods of manure application.

Farm size and its influence on farmer adoption of technologies has been widely studied, especially in cropping systems; however, no universal conclusions have been reached about the role that farm size plays in technology adoption, particularly BMPs (Prokopy et al 2008). We find similar evidence for MMS; namely, that there are no consistent effects of farm size on MMS. There is, however, more evidence to suggest that large farms have greater propensity for adopting MMS best practices (although in some cases these associations are not significant, i.e. Buckley et al 2015). In a survey of Louisiana dairy farmers, larger farms with higher milk yield show greater adoption of BMPs (Rahelizatovo and Gillespie 2004a). These facilities were more likely to adopt erosion control practices and more capital intensive waste management systems, but less likely to adopt best nutrient management practices (Rahelizatovo and Gillespie 2004a). Other evidence suggests that larger farms are more likely to store manure and/or process manure in multiple ways, in part because larger dairy farms collected slurry or liquid manure whereas a majority of smaller farms collected solid manure. Regardless of manure solids, scrape systems—including alley scrapers, barn cleaners, and skid steers—were common across all farm sizes (Aguirre-Villegas and Larson 2017). Larger farms are also more likely to use processed manure (Case et al 2017) and adopt modern technologies for manure management (Brock and Barham 2009). Others found that larger farms in the Netherlands were more likely to use separation technology, though such relationships were not deemed statistically significant (Gebrezgabher et al 2015). One study found that larger farms were more likely to be owner occupied, and thus more likely to adopt anaerobic digesters, suggesting the importance of farm size in relationship to other variables of interest (Tranter et al 2011).

Conversely, in some studies, smaller and medium-sized farmers were associated with less frequent adoption of MMS with environmental benefits. Powell et al (2005) found that small farms in Wisconsin were more likely to have difficulty adequately collecting and utilizing manure in environmentally friendly ways (Powell et al 2005). Similarly, evidence from Connecticut dairy farms indicated that medium-sized farms were more likely to over apply manure on fields close to their manure storage as compared to larger farms; however, this was likely related to the fact that larger farms had access to equipment better suited to efficiently transport manure longer distances (Tao et al 2014). Dairy farmers in New York with fewer than 250 cows also indicated less interest in anaerobic digesters on their farms than did larger dairy operators (Swindal et al 2010). However, Welsh et al find that farm size was mediated by other factors related to manure management, such as access to pasture and attitude towards biotechnology, suggesting that farm size itself had little to no influence on farmer interest in anaerobic digester technology and that other factors should be considered (Welsh et al 2010).

One important limitation to note in considering size as a variable mediating dairy MMS is heterogeneity across the literature. Size often being relative, definitions of what constitute small, medium or large vary by context. For example, one paper defines small farms as under 99 animal units (which is equivalent to approximately 76 full-grown Holstein dairy cows), while another paper from the same region applies under 200 cows as the definition for a small farm. This inconsistent definition of the variable further complicates discerning its potential impacts on MMS.

Outside farm size, other factors have also been explored as possible drivers of dairy farmer adoption of MMS. The existing infrastructure on a dairy farm encompasses the physical structures and equipment as well as operational and organizational systems that enable production. Infrastructure plays a significant role in MMS; for example, manure handling, storage and application strategies are all connected and co-determined by operational infrastructure. In many cases manure storage benefits cannot be realized unless they are accompanied by manure incorporation and consideration of quantity and timing aspects when applying it (Dou et al 2001). The types of manure application possible for a given farm are, in turn, inherently influenced by whether the farm separates manure into liquids and solids (Gebrezgabher et al 2015). For example, Buckley found that the use of solid manure storage was correlated with lower adoption of nutrient management practices as compared with farms using liquid storage. They conclude that this may be related to solid storage being associated with older facilities that are less structurally compatible with the adoption of more modern nutrient management technologies. This conclusion indicates that conversion to liquid systems could increase adoption of nutrient management practices (Buckley et al 2015). Results from Iowa and Missouri make similar conclusions, as farmers with liquid systems were more likely to adopt record keeping and manure injection systems (Gedikoglu et al 2011). Importantly, however, research indicates that the cost and feasibility of transitioning to new MMS can be highly variable across farms (Bishop et al 2010).

Other studies found similar results indicating a substantial influence of existing systems or infrastructure on adoption of new MMS. Early modeling studies suggested that the adoption of systems with less potential nutrient leaching depends on equipment and storage capacity (Southgate et al 1980). More recently, 30% of Ontario dairy farmers indicated that their existing MMS was a limiting factor for both expansion of their farm and potential adoption of new technologies (Filson et al 2003). Given that MMS's become rather 'fixed systems', Cabrera et al (2006), found that such inflexibility in their systems prevented some farmers from using climate and weather forecasts that could assist them with nutrient management planning (Cabrera et al 2006).

While we find there is no universal effect of farm size on MMS identified across the literature, there was, however, a notable trend indicating that larger farms are more likely than smaller farms to adopt certain MMS, particularly storage and treatment strategies that require substantial investment in technology or infrastructure. The literature further indicates that farm size interacts with other farm-level factors to impact the likelihood of a farmer choosing specific MMS.

In terms of farm infrastructure, the literature again indicated the prevalence and influence of interconnected systems related to MMS. Some systems were more conducive to adoption of certain MMS; for example, liquid systems were associated with greater adoption of manure nutrient management practices. The literature also indicated that infrastructure can inhibit improvements to manure management. Because every stage of manure management interacts with the other stages, the infrastructure associated with each is often mutually dependent, making it hard to change only one component of MMS. This is related to the finding that MMS often become fixed systems, which impedes adoption of new strategies or technologies.

Several studies have explored the multiple ways in which social relationships and networks may affect MMS adoption by farmers. Social networks at varying scales appear to influence the adoption of practices and manure management by farmers. Contact with agricultural advisors, researchers or other farmers led to more nutrient management and BMPs adopted in Ireland (Buckley et al 2015), the Netherlands (Oenema et al 2011) and Louisiana (Rahelizatovo and Gillespie 2004a). Contact with government agencies, especially the Natural Resources Conservation Service in the United States, is also associated with increased adoption of BMPs among dairy farmers in Louisiana. Social relationships among dairy farmers were critical for successful implementation of manure exchange programs (i.e. exchanging manure between farms that have excess to those that need manure), particularly as they helped to foster respect and communication across farmers (Asai et al 2014a, 2014b).

Perceived social costs and benefits to society and neighbors is another social determinant that can drive adoption of MMS by farmers. Bishop et al found that social motives and the social costs of avoided adoption of anaerobic digesters were significant predictors of anaerobic digester adoption (Bishop et al 2010). Having non-farmer neighbors is also a significant predictor of anaerobic digester adoption in New York, with the potential to reduce odors and promote good neighbor relations being a primary driver (Swindal et al 2010, Welsh et al 2010).

Several articles explored the role of economic factors in adopting MMS. Some studies have found that economic barriers and/or costs are the primary driving factor influencing MMS adoption. In Europe, Hou et al found that economic factors were the largest barriers to technology adoption for manure treatment, with a lack of investment capital (60%), high processing costs (52%), and long payback periods (45%) being the major reasons cited by farmers (Hou et al 2016). Relatedly, a model based on dairy farmer survey responses in the Pacific Northwest of the US indicated that even profit seeking farmers are unlikely to adopt anaerobic digester technology due to uncertainty regarding the profitability of this major investment. The model further indicated that even farmers that recognize the social benefits of anaerobic digester adoption may be averse to adoption because of economic reasons (Bishop et al 2010). One possible explanation may be the option value of waiting, whereby there is an economic benefit in farmers delaying adoption of a significant technology investment as the technology may become cheaper or more efficient in the future (Anderson and Weersink 2014). Economic barriers were found to be particularly important for adoption of manure processing infrastructure for small farms, who have less income and potentially fewer economic resources (Aguirre-Villegas and Larson 2017). The impact of MMS costs in general can have reaching impacts, with 16% of farmers surveyed in Ontario citing that MMS costs were adversely affecting their quality of life (Filson et al 2003).

Other studies found that economic barriers and costs have different effects on MMS adoption. For example, Paudel found that those technologies that were adopted by dairy farmers had on average the highest costs, but such MMS were eligible for cost-sharing incentives funded through the federal government up to a cost threshold (see policy section below for additional information) (Paudel et al 2008). Barrington found that cost was not consistently reported as the primary factor for farmers shifting towards liquid MMS, but it was often second (Barrington and Piche 1992). Instead, some technology shifts may be influenced by debt to asset ratios, with lower levels associated with increased adoption of best management MMS (Paudel et al 2008). Further, some technologies require consideration of both payback periods and income impact assessments. Longer payback periods for adoption of anaerobic digesters were associated with less likely adoption (Strazzera and Statzu 2016), while potential for increased income through energy generation via anaerobic digesters is a significant predictor of adoption across multiple regions (Swindal et al 2010, Strazzera and Statzu 2016).

How and why farmers adopt MMS can be significantly influenced by policy and regulatory structures in a given region. For example, in Europe, dairy farmers cited the policy and regulatory environment as having the most significant impact on their MMS adoption (Hou et al 2016). Others found that awareness of government regulations related to water quality had a significant impact on adoption of nutrient BMPs (Rahelizatovo and Gillespie 2004a).

Incentive programs or government funding support for MMS were explored across multiple regions. The potential cost-share of incentive programs or economic impacts were shown to have significant impacts on potential or actual adoption of MMS (Southgate et al 1980). Low cost-shares are a hindrance to producer adoption of BMPs (Paudel et al 2008), and even nominal costs for voluntary participation in incentive programs can significantly reduce participation rates (Poe et al 2001). Further, additional grant funding from policies could help shift the return on investment portfolio for particularly expensive MMS such as anaerobic digesters (Anderson and Weersink 2014). While studies do suggest that farmer participation in incentive programs is important to drive adoption of expensive MMS (Paudel et al 2008), in at least some cases, previous participation in government incentive programs actually resulted in dairy farmers being less likely to adopt a BMP (manure injection) (Gedikoglu et al 2011). Further, Poe et al found that 22% of dairy farmers would not participate in voluntary water quality programs even if 100% cost-shares were provided for adoption of practices (Poe et al 2001), demonstrating that some farmers simply will not participate in government programs regardless of the potential benefits or costs.

Importantly, some studies indicate caution around incentive programs and regulations overall, as farm and farmer heterogeneity means that policies may not work everywhere for everyone (Powell et al 2007, Oenema et al 2011). This may be particularly true for nutrient management plans and other manure application technologies since these may be field dependent (Tao et al 2014) and have different impacts on nutrient cycling and GHG emissions, suggesting an inherent need for flexibility in policy (Glenk et al 2014). Others advocated that policies need to consider different types of farmers, not just those that might be innovators or early adopters. Further, since farmers are often dual-motive (i.e. making decisions based on multiple drivers or outcomes), policies that address multiple priorities could also be critical (Bishop et al 2010). This may be particularly important as non-adoption of a practice was found to be due to a perceived non-applicability of a specific practice to a specific farm (Rahelizatovo and Gillespie 2004a), which may not be addressed by policy.

Farmers also often cite regulatory uncertainty as a driver of their on-farm behaviors, as this uncertainty can lead to a perception of hostility towards farmers (Ondersteijn et al 2006). Thurow and Holt suggest that policy and regulatory uncertainty influence farmers' propensity to postpone investment in environmentally friendly management practices. Such uncertainties are associated with shifting guidelines, compliance and timeframes, as well as dissonance between federal and state regulations (Thurow and Holt 1997). Finally, at least one study found that just because regulations require a certain practice does not mean that such practices are fully incorporated into farm-level management. Buckley et al found that while farmers in Ireland were doing soil testing to comply with regulations, they were not actually using the results to inform better nutrient management outcomes on their own farms (Buckley et al 2015).

Throughout the literature, contact with agricultural advisors, researchers and other farmers was consistently found to increase adoption of best practices related to manure management. Farmer attitudes toward non-farm factors, such as societal benefits and neighborliness, were also found to be important drivers of adopting certain MMS, especially adoption of digester technologies.

In contrast, economic barriers were consistently found to be one of the most influential factors in farmer decision making related to MMS. Cost was found to be especially prohibitive for smaller farms in the context of adopting manure treatment strategies. Besides the cost of MMS, cost-share programs, debt to asset ratio, payback period and the opportunity for additional income were found to impact farmers' decisions to adopt or not adopt certain MMS.

Finally, the policy and regulatory landscape was consistently found to be an important factor influencing farmer adoption of MMS. Multiple studies identified the need for flexibility within policies to accommodate farm and farmer heterogeneity. It was also found that farmer uncertainty around regulations negatively impacted farmers' decision to adopt improved MMS.

Studies explored the many ways that information and knowledge about MMS can influence on-farm behavior, with varying outcomes. Gebrezgabher et al found that knowledge of manure separation technologies had no significant impact on farmers wanting to use it. The authors thus conclude that knowledge is not a determining factor for future adoption of this MMS (Gebrezgabher et al 2015). Conversely, others concluded that in fact it is a lack of specific technical knowledge related to nutrient content in manure that has prevented farmers from adopting better nutrient management strategies (Smith et al 2001, Tao et al 2014). Still other results suggest a disconnect between what farmers understand and know, and what others think they understand and know. Ingram found that many farm advisors think that farmers lack technical knowledge of soil management and that this lack of knowledge explained, at least in part, why farmers fail to use more sustainable nutrient management practices (Ingram 2008). Instead, Dou et al find that one of the barriers for farmers to use better MMS specific to nutrient management is not because they do not know about manure nutrient testing, but rather, that they do not trust the test results (Dou et al 2001). In the case of anaerobic digesters, one study concluded that the lack of adoption was not about knowledge of the MMS itself, but rather a lack of knowledge about the potential suite of co-benefits that the practice could offer (Strazzera and Statzu 2016).

Individual farmer attitudes toward technology, risk profiles or perceptions of challenges in agriculture are shown to have notable impacts on farmer adoption of MMS. As Wirth et al describe it, these 'cultural' factors can often mediate the policy, institutional, and farm system in which farmers exist and can explain the difference in MMS adoption (Wirth et al 2013). In the studies we identified, there was a consistent finding that receptiveness and a positive attitude towards the potential technology/MMS in question is important for potential adoption (Bishop et al 2010, Swindal et al 2010, Gebrezgabher et al 2015). But attitudes towards factors beyond the practices themselves also have important impacts. Farmers that expressed high concern for environmental impacts were more likely to want to adopt anaerobic digesters (Strazzera and Statzu 2016) and nutrient management practices (Buckley et al 2015). Additionally, farmers with production-oriented and stewardship mindsets were also more likely to adopt more nutrient management practices (Buckley et al 2015). Conversely, Swindal et al found that farmers were typically motivated by more tangible and financial concerns, including the need to control odors and capitalize on manure, than to do the 'good environmental or public good thing' (Swindal et al 2010). A study of Florida dairy farmers found that many felt that other sources of pollution (e.g. human waste) were a greater contributor to nutrient management issues within the region, which could lead to a lack of adoption of practices to mitigate the problem (Cabrera et al 2006). Counter to other studies, risk averse dairy farmers in Louisiana were more likely to adopt BMPs, which the authors concluded could be a form of risk management (Rahelizatovo and Gillespie 2004a). The role of attitudes for driving adoption of MMS (at least exclusively) should be considered somewhat cautiously though. Gedikoglu et al found that farmer's attitudes about potential impacts of manure injection on water quality had no effect on adoption. This led the authors to recommend that a focus on farmer profitability might be a better strategy (Gedikoglu et al 2011).

Farmer and farm-family demographics were correlated with varying levels of adoption of MMS. Research exploring how the age of farmers influences their MMS decision making had mixed results. Older dairy farmers were found to be less likely: to adopt nutrient management practices (Buckley et al 2015), to want to use processed (i.e. acidified or anaerobic digestion) manure (Case et al 2017), and to want to use manure separation techniques (Gebrezgabher et al 2015). Relatedly, Paudel et al found that impending retirement was the most frequent reason for farmers not to adopt BMPs (Paudel et al 2008). Conversely, however, Gedikoglu found that older farmers in Iowa and Missouri were more likely to want to adopt manure injection (Gedikoglu et al 2011). Education levels among farmers were also found to have varying impacts on MMS perceptions and adoption. While studies found that farmers with higher levels of formal education were more likely to adopt manure injection, keep manure records (Gedikoglu et al 2011) and adopt BMPs for manure management (Paudel et al 2008), Gebrezgabher et al instead found that farmers with less formal education were more likely to have positive attitudes about manure separation technologies (Gebrezgabher et al 2015). Finally, the influence of off-farm income, or the income that a farm household draws from non-farming activities, on farmer decision making about MMS also has mixed results. In the context of manure injection technologies, total off-farm income was not correlated with greater likelihood to adopt. Off-farm seasonal employment, however, which more specifically refers to off-farm work pursued by the individual farm operator during seasonal downswings in farming activities, was correlated with greater likelihood to adopt manure injection technologies. This may indicate that income earned by other members of a farm household does not influence manure management decisions, whereas off-farm income earned by farmers themselves does influence these decisions. In the context of labor intensive MMS strategies, such as record keeping, off-farm income had a negative impact on adoption, likely because of the time management associated with such practices (Gedikoglu et al 2011). Buckley et al found similar results in Ireland, where off-farm income was negatively correlated with adoption of nutrient management practices (Buckley et al 2015).

There was substantial heterogeneity across the literature regarding the impact of farmer knowledge, information and attitudes on adoption of MMS. Overall, there was more consistent indication that a farmer's positive attitude towards a specific MMS was important for adoption. Other attitudinal factors, such as towards the environment, were found to play a role in farmers' decision making. Farmers more concerned with environmental issues and stewardship were more likely to adopt nutrient management and manure treatment strategies. However, the literature also indicated that attitudes and knowledge interact with a complex suite of other factors that may mediate manure management decisions. Similarly, the impact of farmer demographic variables seems to interact with other variables in a complex way, making it difficult to discern the impact of demographic variables on MMS within this small body of literature.