Once‑daily Feeding Is Associated With Better Health in Companion Dogs: Results From The Dog Aging Project Part 1
Jun 20, 2023
Abstract A variety of diets have been studied for possible anti-aging effects. In particular, studies of intermittent fasting and time-restricted feeding in laboratory rodents have found evidence of beneficial health outcomes. Companion dogs represent a unique opportunity to study the diet of a large mammal that shares human environments. The Dog Aging Project has been collecting data on thousands of companion dogs of all different ages, sizes, and breeds since 2019. We leveraged this diverse cross-sectional dataset to investigate associations between feeding frequency and cognitive function (n=10,474) as well as nine broad categories of health conditions (n=24,238). Controlling for sex, age, breed, and other potential confounders, we found that dogs fed once daily rather than more frequently had lower mean scores on a cognitive dysfunction scale, and lower odds of having gastrointestinal, dental, orthopedic, kidney/urinary, and liver/pancreas disorders. Therefore, we find that once-daily feeding is associated with better health in multiple domains. Future research with longitudinal data can provide stronger evidence for a possible causal effect of feeding frequency on health in companion dogs.
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Keywords Canine · Canine cognitive dysfunction · Feeding frequency · Healthy aging · Time-restricted feeding
Introduction
For nearly a century, caloric restriction has been known to extend lifespan and delay age-associated pathology in laboratory animals [1–5]. More recently, in both animals and humans, a variety of alternative “anti-aging” diet modalities have been described which are providing new mechanistic insights and potential clinical applications [6]. These diets include intermittent fasting [7, 8], fasting mimicking diets [9, 10], ketogenic diets [11–15], protein or essential amino acid restriction [16, 17], and time-restricted feeding [18–20].
These diets have been most extensively studied in rodents in controlled laboratory settings, due to the ease of administering diets on a specific schedule and an enhanced ability to tease apart the mechanisms through which they act. Time-restricted feeding studies in rodents suggest improvements in several metabolic parameters, including glucose and insulin homeostasis, energy expenditure, hepatic pathology, resistance to different obesogenic diets, and improved circadian rhythm maintenance during aging [21–23]. In one study, mice who experienced time-restricted feeding demonstrated an 11% extension in lifespan [18]. Additionally, several studies demonstrate that caloric restriction and intermittent fasting play a protective role in maintaining and enhancing cognitive function, including memory and spatial learning [24–28]. It remains unclear, however, whether these benefits in laboratory animals are generally due to reduced caloric intake or meal frequency, or both [6].
Despite the mainstream popularization in humans of several of these diets, the beneficial health effects of time-restricted feeding outside of a laboratory setting are less clear. In some human studies, only mild improvements in body composition and cardiovascular risk factors were detected [29], even when subjects also reduced their daily caloric intake [30]. In other studies, detrimental effects on glucose homeostasis were observed with time-restricted feeding [31]. Finally, while some studies have found potential cognitive benefits, especially for memory in older adults [32, 33], other studies have shown no effect of fasting on cognition [34, 35].
Companion dogs provide a potentially powerful animal model to elucidate the relationship between diet and age-related health outcomes [36]. Having co-evolved alongside people for thousands of years [37], companion dogs share human environments, experience similar diseases, and receive similar medical care. Once-daily feeding in dogs serves as a natural model for the intermittent fasting/time-restricted feeding protocols currently being studied both in preclinical rodent models and in human trials [38].
The Dog Aging Project is a large-scale research initiative following thousands of companion dogs over their lifetimes to better understand how biology, lifestyle, and environment impact healthy aging [39, 40]. Participating owners report annually on a variety of aspects related to their dog’s diet, primary and secondary activities, social and physical environments, medications, and health conditions. In the current study, we used cross-sectional data collected in the first year of the Dog Aging Project to ask if feeding frequency is associated with cognitive function and health conditions. Specifically, we hypothesized that dogs fed once a day would display lower rates of physical health issues and better cognitive scores compared to dogs fed more frequently.
Methods
Subjects
All dogs had been recruited to join the Dog Aging Project (DAP) via mainstream media, social media, or word of mouth. Their owners then completed the relevant online surveys between December 26, 2019, and December 31, 2020 [41]. Study data were collected and managed using REDCap electronic data capture tools hosted through the DAP [42, 43]. REDCap (Research Electronic Data Capture) is a secure, web-based software platform designed to support data capture for research studies, providing (1) an intuitive interface for validated data capture, (2) audit trails for tracking data manipulation and export procedures, (3) automated export procedures for seamless data downloads to common statistical packages, and (4) procedures for data integration and interoperability with external sources.
Instruments
The first survey that participants completed was the Health and Life Experience Survey (HLES), which collects information regarding dog demographics, physical activity, environment, dog behavior, diet, medications and preventives, health status, and owner demographics. In the current investigation, we were principally interested in feeding frequency and health status, and we identified a priori health conditions that could plausibly be affected by feeding frequency.
After completing HLES, all participants were offered the opportunity to complete the Canine Social and Learned Behavior Survey (CSLB), which measures cognitive function. The CSLB, renamed by the DAP, is the same as the Canine Cognitive Dysfunction Rating Scale (CCDR) [44], with only a handful of minor wording changes. The CCDR has been validated as a clinical instrument to detect cognitive dysfunction over a specific threshold. In this work, we use CSLB as a quantitative score for detecting deterioration toward cognitive dysfunction and acknowledge that it is not yet validated for this purpose. The Canine Cognitive Dysfunction Rating Scale was presented to participants as the Canine Social and Learned Behavior Survey to avoid the negative connotations of the phrase “cognitive dysfunction.” This instrument asks owners to indicate the frequency with which their dogs exhibit behaviors indicative of dementia (i.e., disengagement from social activity; difficulty in navigation, searching, and recognition). Based on owner responses, dogs receive a score that ranges from 16 to 80, where higher scores are indicative of worse cognitive function (i.e., more cognitive dysfunction).
During the study period, 27,541 DAP participants completed HLES, and 20,096 DAP participants completed CSLB.
Ethical note
The University of Washington IRB deemed that recruitment of dog owners for the Dog Aging Project, and the administration and content of the DAP Health and Life Experience Survey (HLES), is human subjects research that qualifies for Category 2 exempt status (IRB ID no. 5988, effective 10/30/2018). No interactions between researchers and privately owned dogs occurred; therefore, IACUC oversight was not required.
Inclusion/exclusion criteria
Given that meal frequency is adjusted as puppies mature, we specified the age of inclusion as 1≤age<18 years for all health outcomes. For the CSLB outcome, we specified the age of inclusion as 6≤age<18 years, as 6 years is the youngest age indicated in the literature where signs of cognitive decline can start to appear in dogs [45–47]. Less than 5% of dogs in the DAP are intact, and these dogs were excluded, as well as dogs (<1%) whose owners reported that their diet was “not at all consistent.” Thus, in our final sample, all dogs were spayed or neutered due to exclusion criteria, and slightly less than half of the dogs were male. About one-fifth of dogs received daily or more frequent omega-3 or other fatty acid supplementation in their diet.
We studied health conditions that were reported in the nine broad categories on HLES that could plausibly be affected by feeding frequency: dental or oral disease, skin disorders, orthopedic disorders, gastrointestinal disorders, cancer or tumors, kidney or urinary disorders, cardiac disorders, neurological disorders, and liver or pancreas disorders. The other broad categories of health conditions reported in HLES were not analyzed because they were either based on temporary situational and/or environmental factors and thus unlikely to be associated with feeding frequency (e.g., trauma, ingesting toxic substances, infectious or parasitic disorders), were infrequently reported and thus had a very small sample size (less than 3.5% of the total sample; e.g., respiratory disorders, endocrine disorders, reproductive system disorders, immune-mediated disorders, and hematopoietic disorders), or there was no compelling rationale as to why feeding frequency would affect them (e.g., ear, nose, and throat disorders, eye disorders).
For the health categories examined in this investigation, all participants were assigned a binary score (affected/unaffected). Dogs were considered “affected” if their owner reported them to have at least one relevant condition within a given category. However, we did not consider any congenital health outcomes as affected: since animals were born with these conditions, their feeding regimen was by definition instituted after onset and could therefore not have affected the development of the condition. Similarly, disorders linked to transient situational factors, including infectious diseases and trauma, were not considered as affected, as the circumstantial nature of these instances made them unlikely to be affected by feeding frequency
See Supplementary Information 1 for details of all inclusion/exclusion criteria, as well as the specific conditions that qualified a dog as affected within the dental or oral disease, skin disorders, orthopedic disorders, gastrointestinal disorders, cancer or tumors, kidney or urinary disorders, cardiac disorders, neurological disorders, and liver or pancreas disorders categories.
After applying exclusion criteria, the final sample consisted of responses from 24,238 HLES surveys and 10,474 CSLB surveys. The CSLB was always completed at least 1 week after the completion of HLES. Most participants in the final sample (88%) completed CSLB within 3 months of completing HLES and always within a year (range: 7 to 352 days, average: 47 days).
Explanatory variables
We analyzed feeding frequency as a binary exposure, comparing dogs fed once daily to dogs fed more frequently. Specifically, owners were asked, “How many times per day is your dog fed?” The dogs of owners who answered “Once” were sorted into the once-daily category, whereas the dogs of owners who answered “Twice”, “Three or more,” or “Free-fed (filling up bowl when empty or always having food available)” were sorted into the fed-more-frequently category. In all analyses, 8% of the total sample was fed once daily (Tables 1 and 2).
In our analyses, we adjusted for sex (spayed female or neutered male), age, breed for purebred dogs, and body size (as captured by weight) for mixed-breed dogs. We also adjusted for whether the owner reported daily omega-3 (or another fatty acid) diet supplementation for all analyses except for dental/oral disorders and liver/pancreas disorders, as there is evidence in the literature that fatty acids can have beneficial effects on cognitive function, skin, cardiac, gastrointestinal, renal, orthopedic, and neoplastic outcomes [48–56]. For analysis of CSLB, we additionally adjusted for two factors that are thought to affect cognitive function: physical activity level [57] and whether the dog has a history of training (according to the dog’s primary or secondary activity indicated by the owner; e.g., show dogs, service dogs, and dogs trained for field trials vs. pets/companion dogs; see Supplementary Information 2 for full details) [58].
We adjusted for the breed of purebred dogs as a categorical variable. After inspecting the distribution of weight by breed, we subdivided standard poodles into two breeds for the analysis, large poodles (weight≥13.6 kg (30 lb)) and small poodles (weight<13.6 kg (30 lb)). Although there are over 200 breeds represented in DAP data, for each analysis, we only included breeds that had at least one exposed and one unexposed dog because breeds without variance in the exposure cannot inform the exposure-outcome association. We also restricted our analyses to breeds with at least 10 dogs meeting the inclusion criteria. These restrictions reduced the number of breeds to 76 breeds for the CSLB analysis and 100 breeds for the analyses of health outcomes.
Statistical methods
All statistical analyses were carried out in R v.4.0.3 [59]. Age was flexibly modeled using natural splines with interior knots at 7, 10, and 14 years for CSLB analysis and interior knots at 2, 7, and 13 years for health outcomes [60]. Weight was similarly modeled using natural splines with interior knots at 14, 48, and 79 lbs. In each instance, interior knots are at approximately the 10th, 50th, and 90th percentile of each variable. We explored more elaborate adjustment models (e.g., 4 or 5 interior knots), but these were not supported by metrics such as AIC, and examination of some results suggested overfitting.
To adjust for physical activity, we performed principal component analysis on three HLES-reported activity variables: lifestyle activity level (reported as not active, moderately active, or very active over the past year), average activity intensity level (reported as low: walking, medium: jogging, or vigorous: sprinting, such as playing fetch or Frisbee), and average daily time spent physically active (reported in hours and minutes). The parallel analysis recommended retaining one principal component. This principal component captured 52% of the variance, and we used the loadings onto the first principal component as a physical activity score (PA-score). We adjusted for the PA score using natural splines with interior knots at approximately the 10th, 50th, and 90th percentiles.
Mixed breed dogs were included as a separate category of breed, and we adjusted for body size, as measured by weight, for mixed breed dogs only by constructing a variable weight*MB where weight is the dog’s weight and MB=1 for mixed breed dogs and MB=0 for purebred dogs. This is analogous to grouping mixed breed dogs by weight and including each group as a breed, except that our approach uses continuous weight information.
We used linear regression for the analysis of CSLB and logistic regression for the analysis of all health outcomes. For linear regression, the large number of parameters in the model due to 76 breeds does not cause statistical issues. However, large models are problematic for logistic regression when using conventional maximum likelihood model fitting [61]. Therefore, we ft the logistic models using a conditional likelihood, where the conditioning was on the breed categories. This approach allowed the breed to be in the model without necessitating the estimation of 100 breed parameters. Due to the large size of the dataset, maximizing the exact conditional likelihood was not computationally feasible, and we used the Efron approximation (reported in Supplementary Information 3). We used robust standard error estimates for all regression analyses. All hypothesis tests were two-sided and we did not adjust for multiple comparisons.
For analysis of CSLB, we performed a sensitivity analysis excluding 2% of dogs with scores<20 (n=10,288), as these very low scores are implausible and highly suggestive that the owner did not recognize that some survey questions reflected a bidirectional rather than a unidirectional scale.
For analysis of the nine categories of health conditions, we repeated the analysis using only mixed breed dogs and dogs from the 10 most common breeds, fitting the model with ordinary logistic regression. The 10 most common breeds were Australian shepherd, beagle, Border collie, Chihuahua, dachshund, German shepherd, golden retriever, Labrador retriever, poodles (large), and pugs (Table 2). We also treated these analyses as secondary analyses to assess the robustness of our findings, including robustness given the use of the Efron approximation for the primary analyses.
For all ten outcomes, we repeated our primary analyses but analyzed feeding frequency as a four-level unordered categorical factor.
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