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Social integration and support can have profound effects on human survival. The extent of this phenomenon in non-human animals is largely unknown, but such knowledge is important to understanding the evolution of both lifespan and sociality. Here, we report evidence that levels of affiliative social behaviour (i.e. ‘social connectedness’) with both same-sex and opposite-sex conspecifics predict adult survival in wild female baboons. In the Amboseli ecosystem in Kenya, adult female baboons that were socially connected to either adult males or adult females lived longer than females who were socially isolated from both sexes—females with strong connectedness to individuals of both sexes lived the longest. Female social connectedness to males was predicted by high dominance rank, indicating that males are a limited resource for females, and females compete for access to male social partners. To date, only a handful of animal studies have found that social relationships may affect survival. This study extends those findings by examining relationships to both sexes in by far the largest dataset yet examined for any animal. Our results support the idea that social effects on survival are evolutionarily conserved in social mammals.
Study subjects were members of a well-studied population of wild baboons living in the Amboseli ecosystem in southern Kenya [53]. Subjects were females that had survived to reach adulthood, living in eight different social groups over 84 group-years (average years per group = 10.5; range = 2–16 years). Behavioural and demographic data on each group were collected by three experienced observers during 5-h monitoring visits. These visits occurred year round, two to three times per week per group. For 93% of the females in our main dataset (190 of 204), ages were known to within a few days; for the remaining 14 females (born before the onset of behavioural monitoring), birthdates were estimated to within 1 year (n = 6), 2 years (n = 1) or 3 years (n = 7). Death dates were known to be within a few days for females that died before the end of the study period. For females, adulthood was defined by the onset of menarche; males were considered adult when they became higher ranking than all adult females and ranked among the adult males in their social group [54]. We constructed two individual-based, age-specific indices of adult female social connectedness: one to adult females (SCI-F) and the other to adult males (SCI-M). In studies of the adaptive and health significance of social behaviour, affiliative social connectedness has been measured in a variety of ways (e.g. [1,11–13,15,16–19,40]). We chose to use ‘composite’ indices of social connectedness (as opposed to ‘dyadic’ indices (e.g. [11,12,17]) because we were interested in the effects of a female’s overall level of affiliative social behaviour, regardless of the presence or quality of particular social bonds in her life. Our indices were very similar to those used in several prior studies in non-human animals [14,16,53], as well as those used to measure structural social integration in many studies in humans (reviewed in [1]). Specifically, social connectedness was measured for each female relative to all other adult females alive in the population in the same year. Following previous studies [12,14,15,54], these indices used data on grooming behaviour, which maintains and strengthens social bonds in baboons and other primates [55,56]. To measure grooming relationships, we chose to use ad libitum observations of grooming [57,58], which included all observed instances of grooming between group members and was the densest dataset available to measure patterns of female affiliation (see the electronic supplementary material). Our sampling protocol was designed to avoid potential biases in the grooming data that could result from uneven sampling of study subjects. Specifically, the great majority of our ad libitum data were collected during random-order focal animal sampling on adult females and juveniles, which ensured that observers continually moved to new locations within the group and observed all adult females and juveniles on a regular rotating basis. Ad libitum grooming frequencies were significantly correlated with hourly rates of grooming from focal animal sampling (see the electronic supplementary material), indicating a lack of strong or systematic bias in the ad libitum data. Nevertheless, we could not assess whether our analysis choices completely eliminated biases introduced by our sampling protocol; therefore, we also consider possible implications of these choices in the Discussion. From the ad libitum data, we calculated SCI-F and SCI-M for each adult female in each year of her adult life as a composite index of the relative frequency that she groomed and was groomed by adult females or adult males, respectively (see the electronic supplementary material, figure S1). Positive SCI values represent females with relatively high frequencies of grooming for the population in that year; negative values represent females with relatively low frequencies of grooming for that year. Data to replicate our analyses have been uploaded to the Dryad data repository. We modelled survival in adult females using Cox proportional hazards models. We employed time-varying covariates in our models because, in the course of testing predictors of SCI-F, we found that older females generally had lower values of SCI-F, making it inappropriate to use a single, average value of lifetime social connectedness. We ran two different models using the rms package [59,60] in R [61]. The first model, called the ‘main’ model, included 1968 female-years of data on 204 females with 87 censored records (censored records were females who were still alive when our records ended in 2011; average number of years of data per female = 9.64; range = 1–24 years). The main model included imputed values for some predictor variables in 30% of female-years. Missing values were imputed via multiple imputation [62] and weighted predictive mean matching as implemented via the aregImpute function in the rms package in R [59,60] (see the electronic supplementary material for additional information on data imputation methods). We performed the full imputation 50 times to create 50 imputed datasets and fit the main Cox proportional hazards model to each of these 50 datasets. Parameters presented in the main model were averaged over the 50 model fits. The second model, called the ‘complete case’ model, excluded all female-years with missing data. This model included 1376 female-years of data on 194 females, with 124 censored records. The complete case model had more censored records than the main model because one or more predictor variables were missing for some females in the final year(s) of their life, forcing us to truncate their data prior to the year of their death (N = 37 of 124). For both the main and the complete case models, females entered the model at adulthood and left the model at death or censorship. For both models, we included the following predictor variables: (i) the female’s SCI-F in that year, (ii) her SCI-M in that year, (iii) her average dominance rank in that year, (iv) her average group size (the number of adults of both sexes in the group in that year), (v) whether her mother was still alive and present in the group in that year, and (vi) whether she had adult daughters living in the group that year. For each of these predictors, the validity of the proportional hazards assumption was well supported (electronic supplementary material, table S1). There were no differences in the results from the main and complete case models; in the text, we present the results of the main model because of its added statistical power (see the electronic supplementary material for results of the complete case model). Because we found strong effects of SCI-F and SCI-M on female survival, we conduced further analyses to understand which factors predicted individual SCI-F and SCI-M. Based on prior research, we expected that female social connectedness to adult females would be correlated with the availability of adult maternal kin, who often form the strongest social bonds in baboon societies [63–66], as well as age, which is associated with declining availability of non-kin social partners [64]. We further predicted that female social connectedness to adult males would be correlated with female dominance rank, based on evidence that male ‘friends’ may be a limited resource for female baboons [41,50,67]. We modelled SCI-F and SCI-M separately using linear mixed effects models constructed in the lme4 package in R [68]. Female identity was included in the models as a random variable; we also included the following variables for each female in each year of her adult life: (i) age; (ii) average dominance rank; (iii) average group size; (iv) whether her mother was present in the group; (v) number of her adult maternal sisters in the group; (vi) number of her adult daughters in the group; and (vii) her social connectedness to the other sex (i.e. SCI-M in the case of the SCI-F model and vice versa). We present the results of the full models, but also used stepwise elimination and likelihood ratio tests for subsequent model selection.
