CORRELATES OF LIFE SATISFACTION AMONG MIDDLE-AGED AND OLDER BLACK ADULTS

Abstract This study explored satisfaction across life domains (e.g., family, daily life, health, finances, city of residence) and correlates of satisfaction across domains. Black adults (n=93, age range=55-80) completed the domains of life satisfaction scale and measures of sociodemographic factors, personality, and mental/physical health. Participants’ satisfaction was highest for home condition, but lowest for health. Univariate analyses of variance demonstrated better life satisfaction in the oldest-old (80+) than the youngest-old (55-64; p<.05), particularly in the domains of daily life/leisure, current financial situation, and total household income. Linear regression models suggested that higher satisfaction was associated with less education, less financial strain, lower depressive symptoms, and better self-rated physical health, although the pattern of results varied by domain. Satisfaction may increase with advancing old age, at least in some life domains. It can also vary across life domains and unique factors likely relate to satisfaction in each life domain.


Introduction
Well-being is an important indicator of successful aging and longevity [40,46]. Life satisfaction is one such factor of wellbeing that has received great attention [41] and is higher in older Blacks compared with older Whites [10,42]. These higher levels of life satisfaction are intriguing especially considering Blacks commonly experience social disadvantage [10,43], adverse health outcomes [2,61], higher risk for cognitive impairment [66], and higher risk for functional limitations or disability [22]. These observations prompt the question as to whether life satisfaction may be an important source of resiliency within older Blacks despite the exposure to these adversities.
Prior literature suggests that life satisfaction is associated with sociodemographic factors (e.g., age, income, and personality) [13,23,34,39,48,51] and health [13,23,34,35]. Specifically, poor life satisfaction has been associated with disability, increased psychological distress, pain, poor sleep, negative health behaviors (e.g., smoking and/or drinking) [53], and early mortality [26]. Black adults report high levels of life satisfaction [38,56], which is associated with older age [31,38,56], being married [38,56], higher income [56], being a resident in the South [56], fewer health problems [56], greater frequency of contact with family [38], subjective closeness with family [38,56], lack of need to be assisted from extended family ( [56];), and greater frequency of church attendance [56]. However, to the authors' knowledge, research has yet to examine the combined effects of several of these important factors on different domains of life satisfaction, rather than the Electronic supplementary material The online version of this article (https://doi.org/10.1007/s40615-020-00884-7) contains supplementary material, which is available to authorized users. commonly used broad measurement of life satisfaction as a whole among Black older adults.
As such, another gap in the literature is the operational definition for life satisfaction. Life satisfaction is often derived as a global index, which provides information on life satisfaction as a whole [52]. However, focus on an overall score may mask important specific sources that drive an individual's well-being. Considering that the biopsychosocial model suggests that adults' perceptions of health, well-being, and quality of life are influenced by unique and interacting physical, psychological, cognitive, and social processes [17,28], the next systematic step is to understand satisfaction at the domain level. This approach may be particularly beneficial for understanding health and well-being within our minority groups, as individuals from different sociocultural groups may have different cultural experiences, values, and goals that shape the emphasis they place on specific life domains [32]. For example, older age in Black adults is related to high levels of life satisfaction as a whole [31,38,56]; however, further exploration of underlying subdomains of this global finding would further clarify whether older age is related to a specific source that drives an individual's well-being (e.g., family life) or multiple sources that influence well-being (e.g., family life, leisure activity, and health). Thus, evaluating the domains of life satisfaction may provide rich information to specific individual needs to further guide community-level initiatives, health-related programs, and/or interventions that tap into relevant life domains to enhance the quality of life within older Blacks.
The present study explores satisfaction across eight domains of life (i.e., condition of the home, city of residence, daily life/leisure, family life, current financial situation, total household income, health, and life as a whole) among middleaged and older Blacks. Additionally, the study examines the relationships between satisfaction across each life domain and (1) sociodemographic factors (e.g., age, sex, socioeconomic status, and personality); (2) mental health (e.g., psychological and cognitive indices); and (3) physical health (e.g., health conditions, perceived health, activities of daily living, and blood pressure).

Participants
This study included data from the Tampa Study which was initiated to assess cognitive function and health in Black adults residing in the Tampa, FL area, between October 2014 and June 2016. The Tampa Study recruited 112 community-dwelling self-identified Blacks aged 55+ from health fairs, senior recreation centers, churches, and participant referrals. Participants were considered eligible based upon the criteria including (1) score of 25 or higher on the Mini-Mental State Exam (MMSE; [16]); (2) no indication of significant depressive symptomology as indicated by a score below five on the Geriatric Depression Scale 15-item short version scale (GDS; [65]); and (3) no report of diagnosis of dementia or mild cognitive impairment. A more detailed description of the study has been previously published [20]. This study includes the data of 93 eligible adults from the Tampa parent study with complete data.

Measures
Satisfaction with Domains of Life Life satisfaction was measured using the Satisfaction with Domains of Life (SDL) scale adapted from prior research [32]. The SDL consists of eight items that assess eight domains of life satisfaction on a 5-point scale (1 = completely satisfied, 5 = not at all satisfied). The questions asked: "In your life and your situation right now, how satisfied are you with the/your…" (1) home condition, (2) city or town of residence, (3) daily life/leisure, (4) family life, (5) financial situation, (6) total household income, (7) health, and (8) life as a whole. Item response scores were reverse coded, so higher scores across the domains reflected higher satisfaction.
Demographics Participants' age and sex were documented. Education quantity was measured by asking participants to report how many years of education they obtained. Objective education quality was measured by using the reading subtest of the Wide Range Achievement Test-3rd Edition (WRAT-3) [63], which is a sensitive measure of education quality [33]. The WRAT-3 has a potential maximum score of 57, with higher scores reflecting better education quality. Income was measured by asking participants to report their total gross family income per month. Financial strain was assessed by asking participants how well their monthly income covered their needs [55]. Participants' responses to this question could range from (3) "Not very well" to (0) "Very well." The Everyday Discrimination Scale is a 9-item questionnaire that assesses the frequency of perceived discrimination or unfair treatment [64] in day-to-day experiences (e.g., frequency of being treated with less courtesy). For each item, responses range from (1) "Almost every day" to (6) "Never." Scores could range from 9 to 54 with lower scores indicating higher perceived discrimination.
Personality Traits The 44-item Big Five Inventory (BFI) [24] was used to measure the five personality factors: extraversion, agreeableness, conscientiousness, neuroticism, and openness. Participants were asked the question: "I see myself as someone who…(item description)" and asked to rate on a 5-point scale how well they (1) disagreed strongly to (5) agreed strongly with the description. Higher scores indicate higher levels of each respective factor.
Mental Health Depressive symptoms were measured by the 15-item short form version of the Geriatric Depression Scale [47]. The 14-item Perceived Stress Scale [12] was used to measure the stressful feelings and thoughts within the past month. Subjective mental health was measured by participants' perception of their own mental health compared with peers. Scores could range from 1 to 6 with higher scores indicating positive perceptions of mental health. Subjective memory was measured by a subjective memory complaints questionnaire [1]. Higher scores reflect greater depressive symptoms, stress, and more memory complaints, respectively.
The performance-based cognitive tests were administered via paper-and-pencil using standard neuropsychological assessment methods, and included eleven tests: (1) [14] for working memory and cognitive flexibility; (6) Progressive Matrices [6] for reasoning; (7) Trails Making Test, Parts A and B [45] and (8) Digit-Symbol Substitution test [60] for speed and attention; (9) Card Rotation task [18] for spatial orientation; (10) Boston Naming Task [25] for language and naming; and (11) Verbal Fluency [25] for executive function. For tasks that measure reaction time (i.e., Trails Making Test, Parts A and B), the scores were reverse coded, so higher values reflected better performance. For all tasks, standardized scores were estimated and a sum score was calculated for tasks that represented each of seven cognitive domains: (1) global status (MMSE and MOCA), (2) speed (Trails and Digit Symbol), (3) memory (BVRT, Digit Span, Alpha Span, and Digit Symbol), (4) attention (BVRT, Digit Span, Trails, and Card Rotation), (5) executive function (Digit Span, Alpha Span, Raven's Progressive Matrices, Trails, and Verbal Fluency), (6) visual orientation (BVRT and Card Rotation), and (7) language (Boston Naming and Verbal Fluency). This approach for estimating each cognitive domain score is consistent with the literature [15,19].
Physical Health Health conditions were estimated by taking the sum of conditions (i.e., diabetes, heart disease, hypertension, asthma, emphysema/COPD, cancer, and stroke), which participants reported were diagnosed by a doctor or nurse [57,62]. Subjective physical health was measured by participants' perception of their own physical health compared with peers. Scores could range from 1 to 6 with higher scores indicating positive perceptions of health. Sleep habits was measured with the 19-item Pittsburgh Sleep Quality Index (PSQI) [8], which assesses seven components, including typical sleep quality, sleep latency, sleep duration, sleep efficiency, sleep maintenance, use of sleep medications, and daytime dysfunction. A sum of the seven components was calculated to represent the global sleep habits score that can range from 0 to 21 with higher scores indicating poor sleep. Resting systolic and diastolic blood pressures was monitored using an oscillometric automated device (A & D model UA-767; Milpitas California) while the participant was sitting. Three simultaneous readings were taken and an average reading was calculated. The average reading for each measurement of blood pressure (systolic and diastolic) was included in this study's analyses. A 17-item questionnaire [29] was used to measure physical functioning based on participants' reports of difficulties in activities of daily living (ADL; e.g., eating and grooming) and instrumental activities of daily living (IADL; e.g., finances and driving).

Statistical Approach
Pearson and Spearman correlations assessed the associations between satisfaction of each of the domains of life and the sociodemographic, mental health, and physical health variables (Tables 1, 2, and 3). For each life domain, a multiple linear regression model was conducted including any significantly correlated sociodemographic, personality, mental/ physical health variable. The regressions were conducted to determine which sociodemographic, personality, and mental/ physical health variable remained significantly associated with life satisfaction in a specific domain after accounting for the covariates (Table 4). All analyses were conducted utilizing SPSS software (version 23).

Results
The current study included 93 participants with a mean age of 67 (SD = 7.40, range = 55-86; see Table 1 for demographic characteristics of the sample). A majority (n = 72; 77%) of the participants were female. The participants' average years of education was relatively high (M = 14.71, SD = 2.87). On average, the sample had a total gross monthly income of $1500 to $1600. Approximately, 38% reported signs of financial strain. On average, participants reported low depressive symptoms (M = 1.40, SD = 1.82) and approximately three health conditions (M = 3.11, SD = 2.01). However, the average PSQI global score (M = 8.10, SD = 3.93) for the study sample was above the clinical cutoff score of 6, which is indicative of poor sleep habits [8]. Participants typically reported feeling satisfied across all the domains but reported the highest levels of satisfaction for home condition (M = 2.10, SD = 1.11) and the lowest levels of satisfaction for health (M = 3.03, SD = 1.11). The current study's demographic characteristics are similar to Census data in terms of a high percentage of

Associations among Life Satisfaction Domains
Most domains of life satisfaction were intercorrelated. The correlations indicated that higher levels of satisfaction in one domain were related to higher levels of satisfaction in another domain (Supplemental Table 1). Non-significant correlations of life satisfaction were observed for the domain of city of residence. Specifically, life satisfaction in city of residence was not significantly correlated with life satisfaction in total household income or health.

Life Satisfaction as It Relates to Participant Characteristics
Age, years of education, income, financial strain, discrimination, and personality traits were correlated with various life satisfaction domains (Table 2). Specifically, increased age was correlated with greater satisfaction in (a) daily life/leisure, (b) total household income, and (c) life as a whole. Given the large age range of the sample, subsequent one-way univariate ANOVA were conducted to examine age groups (midlife, 55-64 years of age; young-old, 65-79 years of age; oldest old, 80 years of age and older) in relation to levels of life satisfaction. Significant age group differences were observed for daily life/leisure (F(2, 90) = 3.25, p = 0.04, η2 = 0.07) and total household income (F(2, 90) = 3.80, p = 0.03, η2 = 0.08). For both of these domains, Bonferroni-adjusted pairwise comparisons suggested that, on average, the oldest-old adults (80 and older) reported higher levels of satisfaction than midlife adults

Life Satisfaction as It Relates to Mental Health
Lower depressive symptoms were consistently correlated with greater satisfaction across all life domains (Table 3)

Life Satisfaction as It Relates to Physical Health
Lower numbers of health conditions were correlated with greater satisfaction in health, but not with any of the other life domains (Table 3)

Unique Correlates of Life Satisfaction Domains
Regression analyses suggested that lower depressive symptoms remained significantly associated with greater satisfaction particularly in the domains of city of residence and life as a whole even after accounting for the other sociodemographics, personality traits, mental health, and physical health covariates (Table 4). Financial strain, but not income, remained significantly associated with greater satisfaction in the domains of current financial situation and total household income after adjusting for other covariates. Reduced years of education remained a significant correlate of greater life satisfaction in family life after adjusting for other covariates. Finally, subjective physical health, but not other metrics of physical health, remained significantly associated with greater life satisfaction in health after adjusting for other covariates.

Benefit of Exploring Life Satisfaction as a Multi-Domain Vs. Single-Domain Construct
Many studies have focused on overall life satisfaction as a single-domain construct [30]. However, the current study explored life satisfaction as a potential multi-domain construct because this approach may allow us to understand how multiple facets of life differentially influence middle-aged or older Black adults' satisfaction with life. The current study's findings suggest that levels of satisfaction do vary across life domains (e.g., family, health, finances). This is supported by results reported by Lim et al. [30], who found that "a single domain of life satisfaction (LS) or overall LS will miss many important aspects of LS as age-related LS is multi-faceted and complicated (p. 12)". Hence, examining life satisfaction as single-domain construct very likely masks meaningful information on the specific aspects of older adults' life that relate to their health and well-being. While satisfaction with life as a whole was associated with levels of satisfaction in the more specific domains, the association with the domain of daily life/leisure had the strongest magnitude. Late-life involvement in meaningful leisure activities may foster community supports [21] and social connectedness [58], which are both associated with greater life satisfaction in older adults [44]. This was particularly true for older adults that engaged in more active leisure pursuits (e.g., volunteerism, involvement in clubs and/or organizations, and traveling), as compared with passive leisure pursuits (e.g., reading, telephoning, watching TV) [11]. Thus, our study supports the significance of programs that promote involvement in active and meaningful leisure activity which have direct and indirect benefits for life satisfaction, particularly in Black adults.

Correlates of Life Satisfaction Across the Domains
Although Black adults are at-risk for experiencing social disadvantage across the life course [59], life satisfaction within older Blacks tends to be higher compared with older Whites [10,42]. These findings suggest that life satisfaction may be a source of resiliency for Black adults. Thus, we sought to expand upon this previous work by attempting to identify correlates of life satisfaction within older Black adults. Prior research exploring this topic has observed that demographic (e.g., age) and social factors (e.g., family closeness) are significantly associated with Black adults' life satisfaction, but the prior work has typically examined life satisfaction as a single broad domain capturing life satisfaction as a whole. While this single domain of life satisfaction is useful, a more refined look at specific factors that underlie this overall finding is warranted, as we present here. Since minority groups may have unique and heterogeneous cultural experiences, strictly focusing on the overall score may reduce the likelihood of understanding these domains from diverse perspectives and potentially identifying various sources of resiliency for Black adults. Furthermore, our study expanded upon existing research by exploring multiple sociodemographic, health, and psychosocial indices that may be associated with these domains. Our results demonstrated that various domains of life satisfaction among older Blacks were associated with demographics (e.g., age, education, financial strain), subjective health ratings, depressive symptoms, perceived stress, better sleep quality and personality traits (e.g., agreeableness and neuroticism). In the regression models, we observed that lower depressive symptoms, less financial strain, less years of education, and subjective physical health were unique correlates of life satisfaction across multiple domains, even after accounting for other sociodemographic, personality traits, mental health, and physical health covariates.
Depressive symptoms, in particular, were the variable most often correlated across the domains of life satisfaction. This finding was intriguing, considering the sample, on average (M = 1.40, SD = 1.82), did not have a GDS total score above the clinical cutoff of 4, which reflects depression risk. This is similar to other work [3]. Together, these findings suggest that depressive symptomology is an important correlate of life satisfaction, even within individuals who do not appear to be at risk for depression. One possible explanation for this depression symptom-life satisfaction association is the higher rate of chronic medical conditions among Black adults may cause somatic symptoms, such as pain, which may lead to an increase of depressive symptomology and ultimately lower life satisfaction [3].
In addition, it is likely that limited or no accessible environmental resources (e.g., transportation and affordable healthcare) may also play a role in the associations among these parameters, which may further explain our observed relationship between depression and satisfaction in the city of residence domain even after accounting for other significant covariates. Additionally, chronic medical conditions coupled with somatic symptoms may also deter individuals from being socially engaged with family/peers or participating in everyday activities, which can also prompt depressive symptomology and lower satisfaction [3]. This latter explanation seems particularly reasonable for the observed association between depression and satisfaction for life as a whole. However, a study that includes these proposed individual and environmental parameters is needed to further disentangle these interconnected patterns.
We observed that less years of education was associated with greater satisfaction in family life, which is inconsistent with prior observations [7]. It is unclear why we observed this unusual finding, but we speculate that older adults with lower levels of education in our sample may use family and social networks to exchange and obtain information and resources, which increases opportunities for intimate bonding with family [4]. Prior work has supported that Black adults' life satisfaction tends to be higher when frequency of contact with family is high [38,56], especially for adults who do not feel particularly close to their family [38]. It is also possible that during younger adulthood, highly educated Black adults are in occupations where they may experience more frequent workplace demands, which may elicit or worsen family strain and lower levels of satisfaction in family life [54]. This potential family strain might spillover into later life, even after retirement, maintaining low levels of satisfaction in family life.
Inconsistent with prior literature [2,66], our findings did not support that levels of life satisfaction are associated with objective indicators of cognitive and physical functioning. One possible interpretation for these inconsistent findings is that within our older Black adults, life satisfaction may not be directly related to these objective measures of health, but indirectly related to these indices mediated through psychosocial factors (e.g., social connectedness and self-efficacy). Furthermore, this indirect association may not be evident in the current project's cross-sectional research design, but rather in a longitudinal research design.

Limitations
Although this study has promising findings, there are potential limitations worth discussing. First, this study's cross-sectional design limits the ability to explore if the levels of satisfaction across the domains are static or dynamic over time. We speculate that levels of satisfaction for some domains, such as health, will likely shift over time more so than other domains, such as city of residence, particularly within an older adult population. However, longitudinal study designs are warranted to explore these potential changes in life satisfaction and the influential factors of these changes, which could improve our understanding of life satisfaction during late adulthood. Second, this study did not include some culturally relevant factors that have previously been shown to be related to life satisfaction in Black adults. For example, religious factors (e.g., church-based emotional support and church attendance) have been associated with greater overall life satisfaction [13,23,56]. As a follow-up to these studies, it would be interesting to explore how the association between religious factors and satisfaction might vary across the life domains included in the current study (e.g., health, family, and leisure activities). Empirical evidence from this research could assist in pinpointing aspects of older Black adults' lives where religious services could be beneficial in strengthening satisfaction within that life domain. Third, the findings observed in our study sample, who tended to be highly educated Black adults, may not be observed in older Black adults residing in other geographic settings or other older minority groups. Given we observed several sociodemographic, personality, and mental/ physical health parameters were associated with the environmental domains (e.g., city of residence and home condition) of life satisfaction, it is also likely that these associations may differ in another geographic location. As such, further research that replicates our study in various geographic locations might improve our understanding of neighborhood characteristics conducive to the older residents' well-being, a desired objective for developing global age friendly neighborhoods [37]. However, the demographic characteristics of this study's older Black adult sample is comparable to the sample characteristics of other studies (e.g., Baltimore Study of Black Aging (BSBA; [9,49]); and Minority Aging Research Study (MARS; [5,27]) that have also focused on health and wellbeing in older Black adults.
Despite these study limitations, the current study illustrates that life satisfaction should be explored as a multidomain construct given the complexity of life for older adults, particularly for older Blacks. By exploring life satisfaction as a single-domain, we are likely masking meaningful determinants and consequences of satisfaction across life domains. We found that satisfaction may increase with advancing old age, at least in some life domains (e.g., daily life/leisure). However, advancing age is not necessarily associated with satisfaction in other life domains (e.g., health). Our study provides some preliminary support that operational definition for life satisfaction would benefit from being modified, particularly as it pertains to older diverse populations.
The evaluation of life satisfaction domains may provide rich information to specific individual needs, which may guide and inform community-level initiatives, health-related programs, and/or interventions designed to enhance quality of life within older Blacks.
Funding This research was supported by Byrd Alzheimer's Institute Small Grants Program (BRD215).
Availability of Data and Material Data can be made available upon request.

Compliance with Ethical Standards
Conflicts of Interest The authors declare that they have no conflict of interest.
Code Availability Non applicable.