Biological,Psychological,and Social Predictors of Longevity Among Utah Centenarians

Abstract

Studies of longevity among centenarians examine biological, psychological, and social factors, yet few consider these components concurrently. This study explores such factors individually and collectively, as they are related to days lived past the age of 100 years. Data from 268 family members of centenarians identified in the State of Utah between 2008 and 2015 were used in negative binomial models predicting number of days lived among the centenarians. Findings suggested that sleep latency (biological), life satisfaction (psychological), and attachment closeness (social) were predictive factors of more days lived within individual models. When considered together, sleep latency and life satisfaction remained significant predictors of days lived. Although biological factors are commonly considered in relation to longevity, this study further indicates that psychological and social factors may play important roles in life expectancy. Further examination is needed to explore how these factors link additionally to active life expectancy.

Keywords

centenarians longevity sleep life satisfaction attachment

As a result of over 70 million people born during the Baby Boom, older adults are the fastest growing segment of the population in the United States (Administration on Aging, 2014). Centenarians, those who live to be 100 years of age or older, are a burgeoning subgroup of the older adult population. They surpass the current life expectancy by 20 to 25 years. There is increasing interest in the life expectancy and lived experiences of centenarians (Hagberg & Samuelsson, 2008). Research on longevity among centenarians has a tendency to lead towards the biological aspects of longevity, such as genetic markers and metabolic processes (Motta, Bennati, Ferlito, Malaguarnera, & Motta, 2005; Perls, Bubrick, Wager, Vijg, & Kruglyak, 1998; Poon et al., 2000; Selim et al., 2005); however, psychological and social factors have also been linked to longevity (Lawrence, Rogers, & Wadsworth, 2015; Nosraty, Enroth, Raitanen, Hervonen, & Jylhä, 2015). Much of the research on this topic has examined biological, psychological, and social factors individually in relation to longevity. As an exception, Hagberg and Samuelsson (2008) examined the collective effect of biological, cognitive, and environmental factors linked with longevity in Swedish centenarians. In their multivariate exploration, they argued that longevity at extreme ages is different from longevity among the general population, suggesting that different factors may predict longevity among centenarians. For example, among those of extreme age, geriatric conditions surprisingly do not always correlate with activities of daily living (ADL; Wu et al., 2012). This study builds on previous research by examining biological, psychological, and social factors, both individually and collectively, as they relate to longevity, drawing from family member responses of 268 centenarians identified in the State of Utah between 2007 and 2015.

Biological Factors Related to Longevity

Various biological factors may be linked to greater longevity, including genetic factors, health factors, and health behavior factors. Regarding genetics, female gender has consistently been associated with greater longevity. Men comprise only about 15% of centenarians, because male mortality is significantly higher at younger ages (Poon & Perls, 2007). Even among centenarians, females tend to live longer (Poon et al., 2000). Although female gender is related to greater longevity, older women may experience greater challenges in their later years than men of the same age (Austad, 2006; Haug & Folmar, 1986). Regarding health factors, recent studies have indicated that ADL and instrumental ADL (IADL), common age-related chronic diseases, hospitalization frequency and length of stay are factors associated with longevity (Engberg, Oksuzyan, Jeune, Vaupel, & Christensen, 2009; Freeman, Kurosawa, Ebihara, & Kohzuki, 2010).

Various health behaviors including better sleep quality, not smoking, exercise, and nutrition have been linked with greater longevity. Regarding sleep quality, Gómez-Olivé et al. (2014) found that feeling unrested during the day was associated with increased mortality risk. Also, Mesas, López-García, León-Muñoz, Guallar-Castillón, and Rodríguez-Artalejo (2010) found that long sleep duration (>10 hours) in older adults was associated with greater mortality. Finally, among a sample of Chinese centenarians, Qiu, Sautter, Liu, and Gu (2011) found that poor sleep quality and too long or too short sleep duration were associated with higher mortality risk. Related to smoking, Nicita-Mauro et al. (2008) found that smoking among centenarians is very rare, and that when present it is correlated with poor health. Similarly, Branch and Jette (1984) found that among elderly women, never smoking was the only health behavior that was significantly related with lower mortality. Regarding exercise and nutrition among centenarians, Li et al. (2014) found that adequate physical exercise and a nutritious diet may be key lifestyle factors in predicting longevity.

Psychological Factors Related to Longevity

Psychological factors involving subjective assessments of well-being can play an important role in predicting longevity. Various studies have found connections between higher happiness and greater longevity (Abel & Kruger, 2010; Bishop, Martin, Macdonald, & Poon, 2010; Diener & Chan, 2011; Lawrence et al., 2015; Veenhoven, 2008), subjective well-being and longevity (Cho, Martin, & Poon, 2015; Diener & Chan, 2011), and life satisfaction and longevity (Bishop, Martin, Poon, & Johnson, 2011; Kern, Della Porta, & Friedmann, 2014). For example, according to a study by Abel and Kruger (2010), positive emotions, measured by smile intensity, are a predictor for longevity. Also, in a study that controlled for many economic, social, and demographic factors, Lawrence et al. (2015) found that overall happiness was related to longer lives among U.S. adults. It is important to note that happiness was closely related to other factors including social relationships and socioeconomic status, which in and of themselves are linked to greater longevity (Veenhoven, 2008). Furthermore, Veenhoven (2008) suggests that happiness predicts longevity among healthy populations by protecting against illness, yet does not tend to cure illness in later life. On a related note, depression levels have been linked to diminished longevity (Margrett et al., 2011; Paulson & Lichtenberg, 2013). In addition, increases in ego integrity and decreases in rumination have shown reduction of depressive symptoms (Lamers, Bohlmeijer, Korte, & Westerhof, 2015).

Social Factors Related to Longevity

Aspects of social life have been linked to health and greater longevity. Psychologist John Bowlby (1969) proposed that the attachment system is influential “from the cradle to the grave” (p. 208). Since then, much research has focused on attachment theory and its practical ramifications from infancy to old age. Avoidant attachment and anxious attachment have been found to be negatively related to well-being in older adults (Kafetsios & Sideridis, 2006) and loneliness in the elderly is related to functional decline and death (Luo & Waite, 2014; Perissinotto, Cenzer, & Covinsky, 2012). Predictably, social support is negatively associated with loneliness and positively associated with the mental health of older adults (Margrett et al., 2011; Martin, Hagberg, & Poon, 1997). Results from another study examining the marital history and living arrangements of centenarians suggests that in very old age, living with a spouse is beneficial for men but not necessarily for women, for whom living alone may be more advantageous than living with a spouse (Poulain & Herm, 2016).

Although centenarians may have small social circles, connections with those close to them may help them live longer. The Socioemotional Selectivity Theory argues that as individuals age, they become more selective with their social energy (Carstensen, 1992). Evidence of this is seen as social circles diminish in size but become stronger for proximal relationships. Beyond being married, centenarians might benefit from connections with children, grandchildren, and pets. Broadly, research has indicated that social relationships are linked with decreased mortality in later life (Holt-Lunstad, Smith, & Layton, 2010). One study among nonagenarians included a social component to assess potential factors that contribute to successful aging (Nosraty et al., 2015). In that study, social aspects of successful aging (which included phone contacts in the past week and meeting with their adult children within the past 2 weeks) were associated with lower mortality 4 and 7 years later. Not having contact with grandchildren can be associated with higher depression in older adults (Drew & Silverstein, 2007). Further, in a study of intergenerational support in China, Li et al. (2014) found psychological benefits of grandchildren providing support to their aging grandparents. Research on the potential benefits of pets is mixed, with some suggesting benefits and others indicating risks with having pets (see Herzog, 2011). In short, various social factors may be linked with increased longevity among centenarians.

This Study

Although biological, psychological, and social factors are critical to understanding longevity, there exists a need for additional holistic research exploring the intricacies of longevity in centenarians. Often, psychological factors cannot be separated from biological or social factors. For example, Cho et al. (2015) found that physical health and social resources had a significant effect on subjective well-being among oldest-old adults (centenarians, nonagenarians, and octogenarians), and subjective well-being is related to longevity (Diener & Chan, 2011). Such associations may differ among the oldest-old, whose lived experience may be qualitatively unique compared to those that do not reach 100 years. Predicting longevity and identifying factors that may be associated with an increased life expectancy among centenarians has important implications for those Baby Boomers that live into extreme later life. This study will build on existing research to study the relationship between biopsychosocial connections with longevity among centenarians.

Given findings in the literature, it was expected that although biological factors will likely be linked with greater longevity, psychological and social factors will also play important roles in later life. Specifically, the following was hypothesized:

Hypothesis 1: It was expected that biological factors, such as female gender, better physical health, and better sleep quality will be associated with greater longevity among centenarians.

Hypothesis 2: It was anticipated that psychological factors including life satisfaction, self-efficacy, and ego strength will be related to greater longevity among centenarians.

Hypothesis 3: It was hypothesized that social factors such as attachment closeness, closeness to a grandchild, and having a pet will predict greater longevity among centenarians.

Method

Sample and Procedures

Participants for this study included family members of individuals ages 100+ (centenarians) who were living in Utah, United States, during the period from 2007 to 2015 (see Table 1). A population of 722 centenarians were identified using public information from the Utah Division of Adult and Aging Services, obituaries, the Social Security Death Index and legacy.com. Using publicly available information from the Internet, family members of those centenarians were identified and invited to participate in this study by completing a brief survey about their centenarian family member. Family members were surveyed instead of centenarians because most of the centenarians had already died before this study was conducted. It was specified in the survey that family members should tailor their responses to the last month of the centenarian’s life if the centenarian was already deceased. A preliminary analysis indicated that the time between death of the centenarian and when the study was conducted was not related to any predictors in the study. Of the 722 potential centenarians, contact information for 548 centenarian family members was located and used to recruit participants. Several potential respondents forwarded surveys to centenarian family members that were more involved or were better able to answer questions in the survey. A total of 268 centenarian family members returned completed surveys, yielding a 37.1% response rate of all known centenarians, and a 48.9% response rate among those we attempted to contact. The deceased centenarians whose family member participated in the study (n = 244) did not differ from nonrespondents for whom we had data (n = 298) in number of days lived, t(540) = −.916, p = .36.

Table 1.

Descriptive statistics of Utah Centenarians Who Lived Between 2007 and 2015 (N = 268).

Variable	M or %	SD	n
Centenarians
Days lived	37,335	668.83	244
Years lived	101.74	1.87	244
Gender			267
Female	77.24%		207
Male	22.39%		60
Race
Non-Hispanic White	96.6%		259
Asian	.1%		2
Hispanic	1.5%		4
Marital history
Ever married	96%		258
Ever divorced	6%		16
Family Members of Centenarians
Residence proximity to centenarian
Lived with	20%		55
Lived within 5 miles of	48%		127
Lived more than 5 miles away	52%		141
Contact frequency with centenarian
Daily	51%		137
Weekly	35%		94
Less than weekly	12%		33

Centenarians in this study ranged in age from 100 to 110 in years and from 36,531 to 40,524 days. The average age of centenarians in the sample was 101.74 years (mean days lived = 37,335), with the distribution being right skewed (standard deviation: 1.87 years; 668.83 days). Most (77.24%, n = 207) of the centenarians were female, indicating gender differences in those that live to 100 in Utah. Consistent with demographic trends in the State of Utah, most of the centenarians were identified as non-Hispanic Whites (96.6%, n = 259), with the remaining centenarians being Asian (.07%, n = 2) or Hispanic (1.5%, n = 4). Over 96% of the sample were reported to have ever married (n = 258) and only 6% (n = 16) were reported to have divorced in their lifetime.

Generally, children of the centenarians were the ones to be contacted to participate as a family member in the current study. Although the specific relationship a family member had with the centenarian was not asked, information about their connection with the centenarian, giving some confidence that their responses match was gathered. Twenty percent of the family members lived with the centenarian and 48% lived within 5 miles of the centenarian. Over 50% of the family members reported to have daily contact with the centenarian, with close to 90% having at least weekly contact with the centenarian. Family members reported to feel fairly close to centenarians (mean = 5.4 on a scale of 1 to 6 with 6 representing extremely close), and to get along fairly well with the centenarian during their centenarian years (mean = 5.5 on a scale of 1 to 6, with 6 representing extremely well).

Outcome Measure

Longevity was assessed by the number of days that a centenarian lived past 100 (that is, past 36,500 days). Days lived were determined by subtracting birth dates from death dates derived from public sources (this variable was not collected from family members of the centenarian). Twenty-four of the centenarians were still living at the time of data collection and so they do not have a value for days lived in our analyses. Statistical models utilized days lived past 100 years as the outcome variable. Also, the age distribution of the sample in years lived is presented in Figure 1.

Figure 1.

Ages of Utah Centenarians.

Biological Predictors

Number of medications, gender, and physical health

Participants reported how many medications were prescribed to the centenarian during the last year (“0” coded as 1, “1–3” coded as 2, “4–9” coded as 3, and “10 or more” coded as 4). Participants indicated gender of the centenarian (“1” coded as male and “0” coded as female), and they were asked to rate their family member’s physical health during their centenarian years. Responses ranged from 1 (poor) to 5 (excellent).

Sleep latency

Sleep latency was measured using one item from the Pittsburgh Sleep Quality Index (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989). The sleep questions in the survey were prefaced with the following: “Please answer the following questions about the centenarian’s sleep habits. If the centenarian is deceased, please answer for the last month of their life.” The question about sleep that was used in the current analysis was the following: “During the past month, how often has your family member had trouble sleeping because they cannot get to sleep within 30 minutes?” Responses to this item ranged from 1 (not during the past month) to 4 (three or more times a week). Higher scores indicated worse sleep latency.

Psychological Predictors

Life satisfaction

Life satisfaction was measured with one item, that asked: “During their centenarian years, how satisfied were they with their life overall?” Responses ranged on a 10-point scale from 1 (not at all satisfied) to 10 (completely satisfied), with higher scores indicating greater life satisfaction.

Self-efficacy

Family members of the centenarians reported on the centenarian’s self-efficacy using five items from the Multidimensional Health Locus of Control scales (Wallston, 2005). Items ranged on a 6-point scale from 1 (strongly disagree) to 6 (strongly agree). An example item is “I was in control of my health.” The self-efficacy subscale had adequate reliability (α = .76).

Ego strength

To measure ego strength, participants answered 11 questions from the Ego Identity Process Questionnaire (Balistreri, Busch-Rossnagel, & Geisinger, 1995). Items assessed ego strength commitment on a 6-point scale ranging from 1 (strongly disagree) to 6 (strongly agree). The measure was prefaced with, “Please indicate how much you think your centenarian family member would agree with the statements listed below . . . .,” and then items were worded in the first person from the centenarian’s perspective. Sample questions included, “I never questioned my vocational goals” and “I had firmly held views concerning my role in the family.” When applicable, items were reverse scored to indicate higher ego strength (α = .68).

Social Predictors

Romantic partner, pet, and close grandchild

Participants indicated whether the centenarian had a romantic partner or pet during their centenarian years. They also reported whether the centenarian had a special connection with any specific grandchild or great grandchild. All responses were coded so that 1 indicated yes and 0 indicated no, resulting in higher scores reflecting having a higher social connection.

Adult attachment

To measure adult attachment, participants answered six questions comprising the closeness subscale from the Adult Attachment Scale (Collins & Read, 1990). The measure was prefaced with, “Please indicate how much you think your centenarian family member would agree with the statements listed below . . . .,” and then items were worded in the first person from the centenarian’s perspective. Items were modified to refer to the past, and some wording was slightly changed to reflect common rather than academic language, and included: “I found it relatively easy to get close to others,” “I did not worry about people getting too close to me,” “I was somewhat uncomfortable being close to others,” “I was comfortable developing close relationships with others,” “I was uncomfortable when anyone got too emotionally close to me,” and “People often wanted me to be emotionally closer than I felt comfortable being.” Responses ranged from 1 (strongly disagree) to 7 (strongly agree). Some items were reverse coded so that higher scores reflected higher attachment. Items in this subscale demonstrated appropriate reliability (α = .85).

Results

Description of the Study Participants

As a biological contextualization, we note a number of characteristics that were reported about Utah centenarians. Around 55% (n = 148) of the centenarians were reported to have used hearing aids. Approximately 52% (n = 141) of the sample had dentures, suggesting that close to half continued into their centenarian years with natural teeth. The most common surgeries among the centenarians included cataract surgery (63.4%, n = 170) and joint replacements (hip replacement was the most common at 17%, n = 46). Perhaps due to joint replacements or other aging musculoskeletal challenges, many centenarians used movement aids: 68% (n = 182) of the centenarians reported using a walker, 43% (n = 115) used a wheelchair, and 32% (n = 86) used a cane. These moving aids were not mutually exclusive, meaning that some days or for some purposes, a centenarian might use a walker, and for other purposes a cane.

Most (79%, n = 212) centenarians had a special connection with a grandchild, and 16% (n = 44) of the centenarians were reported to have a romantic partner during at least a part of their centenarian years. Those connections could contribute to life satisfaction (Veenhoven, 2008). Sixteen percent (n = 43) of the centenarians in our sample were reported to have a pet. Some centenarians in our sample also reported to own modern devices, with 12% (n = 33) having a cell phone and 12% (n = 31) of the centenarians having a computer.

Biological, Psychological, and Social Predictors of Longevity

Regression analysis in Mplus (Muthen & Muthen, 2012) was used to examine biological, psychological, and social factors related to days lived among centenarians. Because the outcome variable of days lived past 100 was right skewed and over dispersed, models were estimated that assumed a negative binomial distribution. Significant dispersion parameters in the models (see Table 2) confirmed the appropriateness of using negative binomial models as opposed to Poisson models. Coefficients from negative binomial models are commonly interpreted as rate ratios after having been exponentiated (Hilbe, 2014; see Table 2). Full information maximum likelihood (FIML) was used to account for missing data in the responses (less than 3% missing in all but sleep latency, which had 7.5% missing). The analytic approach utilized simple models that built up to the complex one presented here. Given the pattern of findings found from zero-order correlations, to multiple regression coefficients, to the negative binomial model, it is clear that the sample was not too small for the model estimated. There were 24 centenarians still living at the time of our data collection and so do not have a value for days lived. Results from models assuming these missing data were similar to models with these respondents excluded from analyses, and as such, final models utilized an FIML approach. The models provided the same pattern of results when these persons’ data were omitted and included. The findings did not change with the addition of these 24 centenarians.

Table 2.

Correlations, Means, and Standard Deviations of Main Study Variables.

	1.	2.	3.	4.	5.	6.	7.	8.	9.	10.	11.	12.
1. Days lived	–
2. Gender	−.02	–
3. No. of medicines	−.11^†	−.07	–
4. Sleep latency	–.19**	−.14*	.21***	–
5. Physical health	.04	.16**	−.19***	−.16*	–
6. Life satisfaction	.14*	.18**	−.20***	−.17**	.56***	–
7. Social efficacy	−.01	.14*	−.15*	−.10	.29***	.24***	–
8. Ego strength	−.01	−.06	−.05	−.12	.06	.07	.20**	–
9. Romantic partner	.00	−.30***	−.09	.07	−.09	−.12*	−.19***	−.01	–
10. Grand child	.09	.12^†	.06	.01	−.06	−.12*	−.09	.03	.03	–
11. Pet	.02	−.03	−.08	.03	−.08	−.04	−.03	.16*	.17**	.09	–
12. Attachment	.11^†	−.00	.11^†	−.24***	.17**	.29***	.16*	.26***	−.06	−.07	−.06	–
Mean (SD) or percent (category)	835 (669)	77.2% (Female)	2.21 (0.71)	2.06 (1.10)	3.58 (1.00)	7.12 (2.43)	4.51 (0.88)	4.76 (0.64)	16.4% (Yes)	79.1% (Yes)	16% (Yes)	5.33 (1.18)

Note. Days lived = days lived past 100 years (36,500 days); grand child = close grand child; attachment = attachment closeness.

*p ≤ .05. **p ≤ .01. ***p ≤ .001. ^†p ≤ .10.

As seen in Model 1 of Table 3, although gender and general health were not predictive of days lived among centenarians, taking a higher number of medications was related at a trend level, with fewer days lived (e^B = .89, p ≤ .10). Also, greater sleep latency was a significant predictor of fewer days lived past 100 (e^B = .87, p ≤ .01). As seen in Model 2 of Table 3, ego strength and self-efficacy were not predictive of days lived, yet higher life satisfaction was a significant predictor of more days lived past 100 (e^B = 1.05, p ≤ .05). As seen in Model 3 of Table 3, having a romantic partner, a pet, or a close relationship with a grandchild were not predictive of days lived among centenarians, yet higher attachment closeness was related to more days lived, although only at a trend level (e^B = 1.09, p ≤ .10). To explore how biological, psychological, and social predictors were comparatively linked with days lived past 100, these were all entered as predictors in Model 4 of Table 3. In this final model, greater sleep latency remained a significant predictor of fewer days lived past 100 (e^B = .88, p ≤ .01), and higher life satisfaction was associated with more days lived past 100 (e^B = 1.06, p ≤ .05). Attachment closeness was no longer statistically associated with days lived in the final model, yet the link between higher closeness to a grandchild and more days lived past 100 approached statistical significance (e^B = 1.27, p ≤ .10).

Table 3.

Unstandardized and Exponentiated (rate ratio) Negative Binomial Coefficients From Biological, Psychological, and Social Predictors of Days Lived Past 100 Years (N = 268).

	Model 1: Bio		Model 2: Psycho		Model 3: Social		Model 4: Combined
	B	e^B	B	e^B	B	e^B	B	e^B
Intercepts	7.29***		6.22***		6.46***		7.07***
Gender	−0.09	.92					−0.13	.88
No. of medicines	−0.11^†	.89					−0.08	.92
Sleep latency	−0.14**	.87					−0.12*	.89
Physical health	−0.01	1.00					−0.06	.94
Life satisfaction			0.05*	1.05			0.05*	1.05
Social efficacy			−0.59	.94			−0.03	.97
Ego strength			0.08	1.09			0.03	1.03
Romantic partner					−0.03	.97	−0.03	.97
Grand child					−0.20	.82	−0.24^†	.79
Pet					−0.01	.99	−0.06	.94
Attachment					0.08^†	1.08	0.02	1.02
No. of free parameters	20		14		20		90
−2 Log likelihood	−3,026.03		−2,970.50		−2,615.84		−4,776.68
Dispersion	0.62***		0.67***		0.67***		0.64***

Note. Grand child = close grand child; attachment = attachment closeness.

*p ≤ .05. **p ≤ .01. ***p ≤ .001. ^†p ≤ .10.

Discussion

Using data from family members of 268 centenarians who lived in the State of Utah, the current study examined biological, psychological, and social factors in relation to days lived past 100 (i.e., past 36,500 days). Although past studies have addressed biological, psychological, and social factors separately in relation to longevity among younger older adults, less is known about their collective influence among centenarians. Furthermore, the current study builds on prior research by exploring aspects of biology, psychology, and social factors that are unique and new in relation to longevity (e.g., sleep latency, social efficacy, ego strength, having a pet). Findings indicated that independently, unique biological, psychological, and social factors were linked with more days lived past 100. When considered collectively, sleep latency and life satisfaction held as significant predictors of longevity. A biopsychosocial approach is useful in understanding various predictors and their relative influence on longevity among centenarians.

Regarding the first hypothesis, findings showed that sleep latency was a robust predictor of longevity. Qiu et al. (2011) concluded that poor sleep quality was associated with a higher mortality risk, and Gómez-Olivé et al. (2014) found that an increased mortality risk was associated with feeling unrested during the day in older adults. In this study, a measure of sleep latency (taking longer to fall asleep) was used, which is different from sleep quality (how well one sleeps) or sleep duration (length of hours slept), and in this way, the current study provides additional information about how sleep challenges may relate to longevity. Sleep challenges in general have received a lot of research emphasis lately, with important links to cognitive (Roberts, Shema, Kaplan, & Strawbridge, 2000), physical (Haack & Mullington, 2005), and social outcomes (Yorgason et al., 2016). Older adults are often more prone to sleep challenges (Roberts et al., 2000), highlighting the importance of sleep and its implications in later life. On the positive end, not having trouble falling asleep may serve as an indication of healthy circadian rhythm patterns and a healthy sleep schedule, which may be important for longevity.

Concerning the other biological predictors, gender and health variables (physical health, number of medications) did not significantly predict days lived. Although female gender did not significantly predict days lived, our sample was 77% female (n = 207), coinciding with research showing that females have greater longevity than men. In addition, prior research has shown that men comprise only 15% of the centenarian population (Poon & Perls, 2007), but in this sample, 23% of the participants were male. In the end, we considered that there were a sufficient number of male centenarians to do a valid gender comparison in this study.

It was surprising that physical health and number of medications were not linked with days lived in our sample. It may be that these health measures were not specific or sensitive enough to capture nuances in centenarian health sufficient to connect with days lived. Alternatively, relatively unhealthy centenarians who needed medications but were unable to obtain them may have been confounded with centenarians who were in relatively good health and consequently needed fewer medications.

Some support for the second hypothesis was found, with results suggesting that family member proxy reports of life satisfaction were a significant predictor of longevity. This finding is in line with previous research (Bishop et al., 2011; Kern et al., 2014; Lawrence et al., 2015) and provides further evidence that subjective well-being is associated with biological outcomes. Although life satisfaction is considered to be an indicator of psychological well-being, life satisfaction may also reflect a centenarian’s satisfaction with social relationships and socioeconomic status, which are also linked to greater longevity (Veenhoven, 2008). Given that life satisfaction remained a statistically significant predictor in the final model suggests its robust association with longevity.

It was hypothesized that self-efficacy and ego strength would be related to greater longevity among centenarians; however, our findings did not support this. Although self-efficacy may be an indicator of independence in extreme old age and ego strength may be an indicator of successfully adapting psychologically in later life (Erickson & Shultz, 1982), these factors were not linked to days lived. One interpretation of this nonfinding is that all or most of the centenarians in our study were perceived to have had fairly high levels of self-efficacy and ego integrity by their family members.

Regarding the third hypothesis, although attachment closeness was a significant predictor of days lived in the social model, it was not in the full biopsychosocial model. This finding suggests that although attachment closeness is an important factor related to longer days lived among centenarians, it may compete with sleep and life satisfaction for some of the same variance in days lived. Future research might consider whether links between attachment closeness and days lived are accounted for by biological or psychological factors (Poon & Perls, 2007).

It was also hypothesized that other social factors, including closeness to a grandchild and having a pet, would predict greater longevity among centenarians. Although it is not too surprising that owning a pet was not a significant predictor, given mixed findings of pets in the literature (Herzog, 2011), it was intriguing that closeness to a grandchild was not related to days lived. It may be that at extreme old age, grandparent/grandchild relationships have become more peripheral to well-being (see Carstensen, 1992). Similarly, grandchildren in their 50s and 60s may be pulled in other directions with their own grandchildren.

Strengths and Limitations

Perhaps the greatest limitation for this study is that data were collected by family members, rather than self-report, and that because the centenarians had died prior to the study, those reports were retrospective. This limitation is particularly important, as direct observations and interactions with living centenarians would likely yield a richer picture connecting various factors with longevity. Despite this limitation, respondents in the study were often primary caregivers of the centenarians, allowing us to gain a somewhat proximal perspective, albeit a proxy assessment. A further limitation is that a number of additional important factors need to be considered in future research, such as spirituality, mental status (dementia in particular), and economic status. Despite these limitations, it is noteworthy that connections were found between biological, psychological, and social factors with days lived. One of the main strengths of this study is that there is information about so many centenarians in the State of Utah. In some regard, the sample is greater than one third of the known population of centenarians for the given time period.

Conclusion

Despite limitations, this study builds upon current literature of biopsychosocial factors and how they predict longevity in centenarians. Individual biological, psychological, and social factors contributed to more days lived in this sample. Findings specifically indicated that lower sleep latency, higher life satisfaction, and higher adult attachment were linked with living more days past 100 years. Centenarians and their caregivers may consider the important contributions of these factors in their lives, as well as ways they might enhance them. Further study is needed to explore how these factors link not only to longevity but also to active life expectancy or healthy time in later life.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was provided by the School of Family Life, Brigham Young University.

Author Biographies

Jeremy B. Yorgason, PhD, is an associate professor in the School of Family Life and the Director of the Gerontology Program at Brigham Young University. His current research efforts focus on later life couple relationships in context of the effects of daily health stressors, managing multiple chronic illnesses, and on grandparent/grandchild relationships.

Thomas W. Draper, PhD, is a professor in the School of Family Life at Brigham Young University. His research interests include dyadic methodologies, social science paradoxes, and extreme longevity.

Haley Bronson, BS, graduated from Brigham Young University in Human Development, with a minor in Gerontology. She is currently working at an assisted living facility and pursuing graduate studies in recreational therapy.

Makayla Nielson, BS, is a master's student in the Gerontology Interdisciplinary Program at the University of Utah. Her work is currently focused on technology and aging.

Kate Babcock, BS, received her bachelor’s degree from the School of Family Life at Brigham Young University. She is currently working as a teacher at a nonprofit educational organization in New York City.

Karolina Jones, a student of family studies with an emphasis in human development at Brigham Young University, interests are adolescent development, adult development and aging.

Melanie S. Hill, MS, is a doctoral student in the Marriage, Family, and Human Development program at Brigham Young University Provo. Her current research focuses on social withdrawal and indices of psychological well-being in later life.

Myranda Howard, a student in the School of Family Life at Brigham Young University, is studying human development with a minor in gerontology.

References

Abel

E. L.

Kruger

M. L.

(2010). Smile intensity in photographs predicts longevity. Psychological Science, 21(4), 542–544. doi:10.1177/0956797610363775

Administration on Aging (2014). U.S. Department of Health and Human Services: Aging statistics. Retrieved from http://www.aoa.acl.gov/Aging_Statistics/index.aspx

Austad

S. N.

(2006). Why women live longer than men: Sex differences in longevity . Gender Medicine, 3(2), 79–92. doi:10.1016/S1550-8579(06)80198-1

Balistreri

Busch-Rossnagel

N. A.

Geisinger

K. F.

(1995). Development and preliminary validation of the Ego Identity Process Questionnaire. Journal of Adolescence, 18(2), 179–192. doi:10.1006/jado.1995.1012

Bishop

A. J.

Martin

MacDonald

Poon

(2010). Predicting happiness among centenarians. Gerontology, 56(1), 88–92. doi:10.1159/000272017

Bishop

A. J.

Martin

Poon

Johnson

M. A.

(2011). Exploring positive and negative affect as key indicators of life satisfaction among centenarians: Does cognitive performance matter? Journal of Aging Research, 2011, 1–10. doi:10.4061/2011/953031

Bowlby

(1969). Attachment and loss: Vol. 1: Attachment. New York, NY: Basic Books.

Branch

L. G.

Jette

A. M.

(1984). Personal health practices and mortality among the elderly. American Journal of Public Health, 74(10), 1126–1129.

Buysse

D. J.

Reynolds

C. F.

III Monk

T. H.

Berman

S. R.

Kupfer

D. J.

(1989). The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Research, 28(2), 193–213. doi:10.1016/0165-1781(89)90047-4

10.

Carstensen

L. L.

(1992). Motivation for social contact across the life span: A theory of socioemotional selectivity. Nebraska Symposium on Motivation, 40, 209–254.

11.

Cho

Martin

Poon

L. W.

(2015). Successful aging and subjective well-being among oldest-old adults. The Gerontologist, 55(1), 132–143. doi:10.1093/geront/gnu074

12.

Collins

N. L.

Read

S. J.

(1990). Adult attachment, working models, and relationship quality in dating couples. Journal of Personality and Social Psychology, 58(4), 644–663. doi:10.1037/0022-3514.58.4.644

13.

Diener

Chan

M. Y.

(2011). Happy people live longer: Subjective well-being contributes to health and longevity. Applied Psychology: Health and Well-Being, 3, 1–43. doi:10.1111/j.1758-0854.2010.01045.x

14.

Drew

L. M.

Silverstein

(2007). Grandparents’ psychological well-being after loss of contact with their grandchildren. Journal of Family Psychology, 21(3), 372–379. doi:10.1037/0893-3200.21.3.372

15.

Engberg

Oksuzyan

Jeune

Vaupel

J. W.

Christensen

(2009). Centenarians—A useful model for healthy aging? A 29-year follow-up of hospitalizations among 40, 000 Danes born in 1905. Aging Cell, 8, 270–276. doi:10.1111/j.1474-9726.2009.00474.x

16.

Erickson

Shultz

(1982). The counselor as gatekeeper: Social interaction in interviews. New York, NY: Academic Press.

17.

Freeman

Kurosawa

Ebihara

Kohzuki

(2010). Caregiving burden for the oldest old: A population based study of centenarian caregivers in northern Japan. Archives of Gerontology and Geriatrics, 50(3), 282–291. doi:10.1016/j.archger.2009.04.008

18.

Gómez-Olivé

F. X.

Thorogood

Kandala

N.-B.

Tigbe

Kahn

Tollman

Stranges

(2014). Sleep problems and mortality in rural South Africa: Novel evidence from a low-resource setting. Sleep Medicine, 15(1), 56–63. https://doi.org/10.1016/j.sleep.2013.10.003

19.

Haack

Mullington

J. M.

(2005). Sustained sleep restriction reduces emotional and physical well-being. Pain, 119, 56–64.

20.

Hagberg

Samuelsson

(2008). Survival after 100 years of age: A multivariate model of exceptional survival in Swedish centenarians. The Journals of Gerontology: Series A: Biological Sciences and Medical Sciences, 63(11), 1219–1226. doi:10.1093/gerona/63.11.1219

21.

Haug

M. R.

Folmar

S. J.

(1986). Longevity, gender, and life quality. Journal of Health & Social Behavior, 27(4), 332–345.

22.

Herzog

(2011). The impact of pets on human health and psychological well-being. Current Directions in Psychological Science, 20, 236–239. doi:10.1177/0963721411415220

23.

Hilbe

J. M.

(2014). Modeling count data. New York, NY: Cambridge University Press.

24.

Holt-Lunstad

Smith

T. B.

Layton

J. B.

(2010). Social relationships and mortality risk: A meta-analytic review. PLoS Med, 7(7), e1000316. doi.org/10.1371/journal.pmed.1000316

25.

Kafetsios

Sideridis

G. D.

(2006). Attachment, social support and well-being in young and older adults. Journal of Health Psychology, 11(6), 863–876. doi:10.1177/1359105306069084

26.

Kern

M. L.

Della Porta

S. S.

Friedman

H. S.

(2014). Lifelong pathways to longevity: Personality, relationships, flourishing, and health. Journal of Personality, 82(6), 472–484. doi:10.1111/jopy.12062

27.

Lamers

S. A.

Bohlmeijer

E. T.

Korte

Westerhof

G. J.

(2015). The efficacy of life-review as online-guided self-help for adults: A randomized trial. The. Journals of Gerontology: Series B: Psychological Sciences and Social Sciences, 70(1), 24–34. doi:10.1093/geronb/gbu030

28.

Lawrence

E. M.

Rogers

R. G.

Wadsworth

(2015). Happiness and longevity in the United States. Social Science & Medicine, 145, 115–119. doi:10.1016/j.socscimed. 2015.09.020

29.

Bai

Tao

Zeng

Han

Luo

Zhao

(2014). Lifestyle of Chinese centenarians and their key beneficial factors in Chongqing, China. Asia Pacific Journal of Clinical Nutrition, 23(2), 309–314. https://doi.org/10.6133/apjcn.2014.23.2.05

30.

Luo

Waite

L. J.

(2014). Loneliness and mortality among older adults in China. Journals of Gerontology Series B: Psychological Sciences & Social Sciences, 69(4), 633–645.

31.

Margrett

J. A.

Daugherty

Martin

MacDonald

Davey

Woodard

J. L.

Poon

L. W.

(2011). Affect and loneliness among centenarians and the oldest old: The role of individual and social resources. Aging & Mental Health, 15(3), 385–396. doi:10.1080/13607863.2010.519327

32.

Martin

Hagberg

Poon

L. W.

(1997). Predictors of loneliness in centenarians: A parallel study. Journal of Cross-Cultural Gerontology, 12(3), 203.

33.

Mesas

A. E.

López-García

León-Muñoz

L. M.

Guallar-Castillón

Rodríguez-Artalejo

(2010). Sleep duration and mortality according to health status in older adults. Journal of the American Geriatrics Society, 58(10), 1870–1877. https://doi.org/10.1111/j.1532-5415.2010.03071.x

34.

Motta

Bennati

Ferlito

Malaguarnera

Motta

(2005). Successful aging in centenarians: Myths and reality. Archives of Gerontology and Geriatrics, 40, 241–251. doi:10.1016/j.archger.2004.09.002

35.

Muthen

L. K.

Muthen

B. O.

(1998-2012). Mplus user’s guide (7th ed.). Los Angeles, CA: Muthen & Muthen.

36.

Nicita-Mauro

Lo Balbo

Mento

Nicita-Mauro

Maltese

Basile

(2008). Smoking, aging and the centenarians. Experimental Gerontology, 43(2), 95–101. https://doi.org/10.1016/j.exger.2007.06.011

37.

Nosraty

Enroth

Raitanen

Hervonen

Jylhä

(2015). Do successful agers live longer? The Vitality 90+ Study. Journal of Aging & Health, 27(1), 35–53. doi:10.1177/0898264314535804

38.

Paulson

Lichtenberg

P. A.

(2013). Vascular depression and frailty: A compound threat to longevity among older-old women. Aging & Mental Health, 17(7), 901–910. doi:10.1080/13607863.2013.799115

39.

Perissinotto

C. M.

Cenzer

I. S.

Covinsky

K. E.

(2012). Loneliness in older persons. Archives of Internal Medicine, 172(14), doi:10.1001/archinternmed.2012.1993

40.

Perls

T. T.

Bubrick

Wager

C. G.

Vijg

Kruglyak

(1998). Siblings of centenarians live longer. The Lancet, 351, (1560).

41.

Poon

L. W.

Johnson

M. A.

Davey

Dawson

D. V.

Siegler

I. C.

Martin

(2000). Psychosocial predictors of survival among centenarians. In Martin

Ch. Rott Habberg

Morgan

(Eds.), Centenarians: Autonomy versus dependence in the oldest old. New York, NY: Springer.

42.

Poon

L. W.

Perls

T. T.

(2007). Annual review of gerontology and geriatrics. Biopsychosocial approaches to longevity ( Vol. 27). New York, NY: Springer.

43.

Poulain

Herm

(2016). Centenarians’ marital history and living arrangements: Pathways to extreme longevity. Journals of Gerontology: Social Sciences, 71(4), 724–733. doi:10.1093/geronb/gbv082

44.

Qiu

Sautter

Liu

(2011). Age and gender differences in linkages of sleep with subsequent mortality and health among very old Chinese. Sleep Medicine, 12(10), 1008–1017. doi:10.1016/j.sleep.2011.04.014

45.

Roberts

R. E.

Shema

S. J.

Kaplan

G. A.

Strawbridge

W. J.

(2000). Sleep complaints and depression in an aging cohort: A prospective perspective. American Journal of Psychiatry, 157, 81–88. doi:10.1176/ajp.157.1.81

46.

Selim

A. J.

Fincke

Berlowitz

D. R.

Miller

D. R.

Qian

S. X.

Lee

Morley

J. E.

(2005). Comprehensive health status assessment of centenarians: Results from the 1999 Large Health Survey of Veteran Enrollees. Journals Of Gerontology Series A: Biological Sciences & Medical Sciences, 60A(4), 515–519.

47.

Veenhoven

(2008). Healthy happiness: Effects of happiness on physical health and the consequences for preventive health care. Journal of Happiness Studies, 9(3), 449–469. doi:10.1007/s10902-006-9042-1

48.

Wallston

K. A.

(2005). Overview of the Special Issue on Research with the Multidimensional Health Locus of Control (MHLC) Scales. Journal of Health Psychology, 10(5), 619–621. doi:10.1177/1359105305055301

49.

Flaherty

Dong

Liu

Deng

Zhang

Malmstrom

T. K.

(2012). Impact of geriatric conditions versus medical diagnoses on ADL disability among nonagenarians and centenarians. Journal of Aging and Health, 24(8), 1298–1319. https://doi.org/10.1177/0898264312457411

50.

Yorgason

J. B.

Godfrey

W. B.

Call

V. R.

Erickson

L. D.

Gustafson

K. B.

Bond

A. H.

(2016). Daily sleep predicting marital interactions as mediated through mood. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences. doi:10.1093/geronb/gbw09