Life Satisfaction among Older Adults in Rural and Urban Mongolia: A Cross-Sectional Survey Study

Biomedicine Hub Research Article Received: May 31, 2023 Accepted: August 29, 2023 Published online: October 25, 2023 Biomed Hub 2023;8:79–87 DOI: 10.1159/000533917 Life Satisfaction among Older Adults in Rural and Urban Mongolia: A Cross-Sectional Survey Study aSchool of Public Health, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia; Department of Information Engineering and Computer Science, University of Trento, Trento, Italy; cSchool of Social Work, Virginia Commonwealth University, Richmond, VA, USA b Keywords Life satisfaction · Loneliness · Mongolia · Rural/urban · Social support Abstract Introduction: Life satisfaction is a strong indicator of wellbeing for older adults. In this study, we aimed to assess the level and correlates of life satisfaction among older adults in urban and rural Mongolia. Methods: We recruited 304 community-dwelling older adults in urban and rural regions of Mongolia. We compared levels of life satisfaction for the two groups, and then used hierarchical regression to examine the association of sociodemographic, health, psychosocial factors, and urban/rural status with life satisfaction. Results: Older adults in urban areas reported higher levels of life satisfaction than their rural counterparts. In the final step of the hierarchical regression model, more grandchildren in the household, better self-rated health, and reporting more positive than negative affect were associated with better life satisfaction at p < 0.05 as were engaging in paid work and lower levels of loneliness at p < 0.10. Net the effects of all other variables in the analysis, older adults in rural areas reported lower levels of life satisfaction. Conclusion: Our findings indicate that living in rural areas of karger@karger.com www.karger.com/bmh © 2023 The Author(s). Published by S. Karger AG, Basel This article is licensed under the Creative Commons AttributionNonCommercial 4.0 International License (CC BY-NC) (http://www. karger.com/Services/OpenAccessLicense). Usage and distribution for commercial purposes requires written permission. Mongolia leads to lower levels of life satisfaction. We identify potential points to intervene through policies, programs, and practices that target the strengths and needs of older adults in rural areas by addressing inequities in socioeconomics, health, mental health, and opportunities for social integration. © 2023 The Author(s). Published by S. Karger AG, Basel Introduction Subjective well-being (SWB) refers to how people evaluate their lives at a given moment and over more extended periods. Life circumstances and dispositional/ construal theories provide complementary frameworks for conceptualizing SWB [1]. Life circumstances theory attributes well-being to advantageous and disadvantageous demographic factors, the number and balance of positive and negative day-to-day experiences, and satisfaction with positive and negative events, experiences, and emotions in important life domains. Dispositional/ construal theories, on the other hand, ascribe SWB evaluations to genetically influenced biological or temperamental factors that affect behaviors and cognitions, i.e., how an individual interprets and appraises their life Correspondence to: Sugarmaa Myagmarjav, sugarmaa @ mnums.edu.mn Downloaded from http://karger.com/bmh/article-pdf/8/1/79/4037876/000533917.pdf by guest on 27 October 2023 Saranchuluun Otgon a, b Denise Burnette c Yerkyebulan Mukhtar a Fabio Casati c Sugarmaa Myagmarjav a Life Satisfaction among Older Adults Self-evaluations of life satisfaction vary by locale and over time. In OECD countries, ratings tend to decline with age, and older adults are less satisfied on average than younger people [9]. Using data from large-scale, nationally representative panel studies in Germany and Britain, Baird et al. [5] (2010) found that life satisfaction decreased little during much of adulthood, then dropped steeply after age 70. British data also showed a relatively significant increase in life satisfaction from the 40s to the early 70s. On the other hand, the Gallup World Poll, an ongoing survey in more than 160 countries, found an oftreported U-shaped association between evaluative wellbeing and age in high-income, English-speaking countries; lowest levels of well-being for persons aged 45–54 years. Findings of higher levels of life satisfaction at advanced ages, when declining health and significant social losses are more common, have led to the so-called “paradox of well-being.” Hudomiet et al. [10] (2020) used 80 Biomed Hub 2023;8:79–87 DOI: 10.1159/000533917 longitudinal data from the US Health and Retirement Study (HRS) to explain this paradox. In cross-sectional data, life satisfaction increased with [10] age beyond retirement into advanced old age; however, longitudinal data showed significant age-related declines in life satisfaction that accelerate with age and widowhood, and health shocks contributed to this decline. The authors reconciled findings from the cross-section and longitudinal measurements by showing that differential mortality and differential non-response bias the crosssectional age profile upward: individuals with higher life satisfaction and those in better health tend to live longer and to remain in the survey, causing an increase in average values. The authors conclude that the optimistic view about increasing life satisfaction at older ages based on cross-sectional data is not warranted [11]. Factors that contribute to life satisfaction and their relative weight also change over the life course, with subjective perceptions becoming more critical. Older adults tend to place less value on status and money and more on family relationships and long-term fulfillment. Self-rated health also appears to have more impact on life satisfaction than objective measures of health. For instance, Puvill et al. [12] (2016) suggest that mental health is a far more robust contributor to life satisfaction than physical health, particularly for the oldest old. In a study of older adults in China, Ng et al. (2017) highlighted physical and cognitive health status as major determinants of life satisfaction, alongside female sex, higher education, perceptions of relative economic status, living with family, living in a city, regular physical exams, access to social security and commercial insurance, and availability of community social services. Also in the region, Gallup World Poll respondents in the former Soviet Union and Eastern Europe reported large and progressive reductions in wellbeing with age [5], while Didino et al. [13] (2018) found that higher quality social interaction, better standards of living and satisfaction with one’s health were associated with greater life satisfaction and happiness among older adults in Siberia. Aging in Mongolia Mongolia is in the early stages of a major demographic transition. Sustained economic and social progress and health system improvements have extended life expectancy at birth from 62.9 in 2000 to 72.7 years in 2022 – yet still below the World Health Organization (WHO) Western Pacific Region average of 76.6 years. As a result of this trend and a rapid decline in the fertility rate in recent decades, the proportion of the country’s population aged 65 and over is projected to increase from Otgon/Burnette/Mukhtar/Casati/ Myagmarjav Downloaded from http://karger.com/bmh/article-pdf/8/1/79/4037876/000533917.pdf by guest on 27 October 2023 circumstances and events [2]. Finally, cultural patterns of individualism and collectivism that help shape the extent to which family and in-group serve as a main reference for thought, feelings, and behavior also influence SWB [3]. Diener’s (1984) widely used tripartite model of SWB comprises life satisfaction, positive affect, and negative affect [4]. Most comparative life satisfaction studies have contrasted the West, especially North America, with East Asia [5]. But a growing appreciation of the complex role of overall well-being as an indicator of broader social progress has extended indicators of life satisfaction well beyond economic conditions [6]. The Organization for Economic Co-operation and Development launched the Fifth edition of Better Life Initiative, which includes measures of constructs in Diener’s SWB model used for population-based survey collects data on multiple indicators of 11 dimensions of current material conditions, quality of life, and their likely sustainability [7]. Measures are then aggregated and used to monitor the well-being of populations and their salient subgroups. With rapid population aging in low- and middleincome countries, older adults represent a crucial subgroup for targeted health, mental health, and social policies and services in these locales. Global measures of life satisfaction serve as a useful indicator and outcome measure for planning, implementation, and evaluation. The current study explores levels and correlates of life satisfaction, defined as the subjective evaluation of one’s overall life [1, 8], in a sample of 304 community-dwelling older adults in Mongolia. Table 1. Proportional quato sampling strategy 4.3% in 2020 to 14% in 2050, while the share of people older than 80 will increase nearly fivefold, from 0.7% to 3.0% [14]. Mongolia faces significant challenges in developing and implementing age-friendly policies and actions that will improve the quality as well as length of life for older adults. Using fixed-effects modeling, Williams et al. [15] (2022) determined that continued investment in the health of older people in Mongolia would improve the quality of life while enhancing the sustainability of public budgets. There is evidence that positive health-related and social outcomes are associated with high levels of flourishing, a eudemonic dimension of psychological well-being, among older Mongolians [16], which suggests that policies and programs should also aim to improve their life satisfaction. Finally, it is important to consider the distribution and needs of socially and economically vulnerable subgroups. Worldwide, the gender gap in life expectancy is 4.2 years (average 68 years for men and 72.2 years for women); this compares to a startling 9-year gap in Mongolia, where there are 2.5 times the number of older women as same-aged men and 69.2% of older adults are women [17]. Older adults are more vulnerable to poverty as most cannot work for pay and their pensions and benefits are insufficient to sustain a healthy livelihood and many lack essential information about potential resources they may need [18]. Loneliness, an inability to access social and health care, and depression are therefore common [19]. Owing to the wide geographic dispersal of the population and poor infrastructure in rural and outlying areas, older adults, including nomadic pastoralists, who live in these areas are likely to be especially disadvantaged. Drawing on life circumstances and dispositional/construal theories, studies on health and psychosocial correlates of life satisfaction in later life, and Mongolian cultural norms and values, we pose three sets of hypotheses: H1: compared to their rural age-peers, urban older adults will report: 1. higher levels of life satisfaction 2. higher levels of physical well-being 3. higher levels of psychosocial well-being H2: net the effects of sociodemographic characteristics of older adults in the sample: 1. physical well-being measures will contribute significantly to life satisfaction 2. psychosocial well-being measures will contribute significantly to life satisfaction H3: net the effects of sociodemographic characteristics, physical and psychosocial well-being, and geographic locale (urban vs. rural) will contribute significantly to life satisfaction. Health and Activities of Daily Living Impairment We assessed self-rated health with a standard question from the World Health Survey (2002): “In general, how would you rate your health today?” (very good = 1; good = 2; moderate = 3; bad = 4; very bad = 5) [22]. Current assistance with personal and instrumental activities of daily living (ADL) was measured as yes = 1 and no = 0 on the following activities: dressing, putting on shoes and socks, walking across a room, bathing or showering, eating, e.g., cutting up food, getting in or out of bed, using the toilet, including getting up or down, using a map to figure out how to get around in a strange place, preparing a hot meal, shopping for groceries, making Life Satisfaction among Older Adults in Rural and Urban Mongolia Biomed Hub 2023;8:79–87 DOI: 10.1159/000533917 Age group Total population Study sample Urban Rural 55–59 60–54 65–69 70+ Total 115,125 65,496 43,089 71,976 295,686 125 71 47 78 322 68 39 25 42 174 58 32 22 36 148 Materials and Methods Measures Dependent Variable A single item from the World Values Survey (OECD, 2013) was used to measure life satisfaction: “Overall, how satisfied are you with life as a whole these days?” (“not at all satisfied” = 0 to “completely satisfied” = 10). The theoretical range was 0–10; higher scores mean greater life satisfaction [20]. Independent Variables Sociodemographic indicators are from the Survey of Health, Aging, and Retirement in Europe (SHARE) [21]. It includes age, sex (male = 1, female = 2), residence (urban = 1; rural = 2), marital status (married or living with partner = 1, single, divorced, or widowed = 2), and employed during the past month (yes = 1; no = 0). Education was classified as illiterate or primary school = 1, secondary = 2, high school = 3, vocational school = 4, and university degree = 5. 81 Downloaded from http://karger.com/bmh/article-pdf/8/1/79/4037876/000533917.pdf by guest on 27 October 2023 Design and Sampling The study used a cross-sectional survey design. As old age thresholds differ by gender in Mongolian law, we used proportional stratified sampling to recruit 210 women aged ≥55 and 94 men aged ≥60 years (N = 304) (Table 1). We recruited older adults who had normal daily self-sufficiency and had lived at their address for more than 1 year. Older adults who were hospitalized at that time were excluded from the study. All participants resided in the community and were recruited from 3 of the 9 districts of the capital city of Ulaanbaatar and two province centers and their subprovinces in the Gobi and Khangai regions. Thirteen trained interviewers with social work and public health training conducted face-to-face, semi-structured interviews of about 30 min durations in elder associations, geriatrician offices, and respondents’ homes. Study participants received 10,000 MNT (~4 EUR) compensation. Table 2. Sociodemographic characteristics of participants (categorical variable) Total (n = 304) Sociodemographics Sex (male = 1) Marital status (married/partner = 1) Education Primary or illiterate Secondary High school Vocational Bachelor or more Paid work (yes = 1) Urban (n = 162) n % n % n % 94 146 30.9 48 50 87 30.9 53.7 44 59 31 41.5 48 53 79 53 70 48 15.8 17.5 26.1 17.5 23.1 15.8 7 17 46 36 56 25 4.3 10.5 28.4 22.2 34.6 15.4 41 36 33 17 14 23 29.1 25.5 23.4 12.1 9.9 16.2 Psychosocial Factors Affect balance was determined by asking respondents how happy, worried, and depressed they felt yesterday, on a scale of 0–10 in each case. We then assessed the mean positive and negative affect scores on the OECD (2013) measure of wellbeing. Following OECD guidelines, we then created an “affect balance” score by subtracting the mean negative affect score from the mean positive affect score, yielding a theoretical range of −10 to 10 [20]. Loneliness: We measured loneliness using the Three-Item Loneliness Scale [23]. “How often do you feel that you lack companionship?” “How often do you feel left out?” “How often do you feel isolated from others?” Items are scored as hardly ever = 1; sometimes = 2, or often = 3, then summed (theoretical range = 3–9). Higher scores indicate greater loneliness. Social isolation was measured by the Mongolian version [24] of the 6-item Lubben Social Network Scale (LSNS-6). This two-factor scale assesses perceived support from family (item 1–item 3) and friends (item 4–item 6). Items are scored from 0 (none) to 5 (nine or more). Total scores are an equally weighted sum of all 6 items (theoretical range = 0–30), and higher scores indicate lower social isolation. Social participation was measured with items from the European SHARE study [21]. Questions ask if and how often a respondent has engaged in 7 types of volunteering, social, and cognitively stimulating activities: volunteering or charity work; caring for a sick or disabled adult; providing help to family, friends, or neighbors; attending an educational or training course; going to a sport, social, or other types of a club; taking part in a religious organization; or taking part in a political or community-related organization. Response options are almost daily = 1; almost every week = 2; less often = 3. Summed scores have a theoretical range of 7–21, and higher scores mean higher levels of social participation. We also asked about household composition, including the number of adult children and number of grandchildren who live in the household. Biomed Hub 2023;8:79–87 DOI: 10.1159/000533917 Degree of freedom χ2 statistic p value 1 1 4 0.001 4.479 64.927 0.982 0.034 <0.0001 1 0.033 0.855 Statistical Analysis We used SPSS (ver.28) for data cleaning and analysis. We generated univariate descriptive statistics for all study variables and conducted bivariate analyses (χ2 and t tests) to assess urban versus rural group differences in correlates of life satisfaction. We then used hierarchical regression to examine the contributions of health and psychosocial measures to life satisfaction by geographic locale. Finally, we tested the association of urban versus rural residence with life satisfaction over and above the effects of demographics and physical and psychosocial well-being measures. Results Table 2 presents descriptive data on study variables, overall, and by urban/rural status. Participants’ average age was 64 years (range = 55–88), 69.1% were female, and 48% were married or living with a partner. Rural residents were less likely to be married χ2(1) = 4.479, p = 0.034. Almost one-quarter of the sample had a bachelor’s degree, and another 17% had vocational training while 16% reported engagement in paid work during the past month. Urban dwellers were better educated than those in rural areas χ2(4) = 64.927, p < 0.0001. They were more than twice as likely to have completed vocational school and almost 3 times more likely to hold a bachelor’s degree. Rural older adults reported more adult children, t (284.36) = 2.156, p = 0.032 but fewer grandchildren living in their households, t (294.36) = 1.953, p = 0.052. The data partially supported our first set of bivariate hypotheses (Table 3). Urban older adults reported higher levels of life satisfaction t (281.48) = 3.046, p = 0.003 and social participation t (302) = 5.952, p < 0.001. However, the two groups did not differ on self-rated health, ADL assistance, affect balance, loneliness, or Otgon/Burnette/Mukhtar/Casati/ Myagmarjav Downloaded from http://karger.com/bmh/article-pdf/8/1/79/4037876/000533917.pdf by guest on 27 October 2023 telephone calls, taking medications, doing work around the house or garden, and managing money, e.g., paying bills and keeping track of expenses. 82 Rural (n = 142) Table 3. Sociodemographic, health, and psychosocial characteristics of participants (numeric variables) Total Rural Degree of freedom T statistics p value M SD M SD M SD 7.56 2.1 7.90 1.93 7.17 2.22 281.48 3.046 0.003 64 0.49 7.1 0.96 63.87 0.59 7.21 1.08 64.16 0.38 6.99 0.81 302 294.36 0.348 1.953 0.728 0.052 2.67 0.62 0.76 1.23 2.7 0.49 0.85 0.92 2.65 0.76 0.68 1.5 302 227.62 0.558 1.836 0.577 0.068 3.09 4.31 3.52 5.64 18.21 1.87 2.16 1.02 4.21 6.04 2.53 4.06 3.42 5.33 17.69 1.82 2.03 0.91 4.41 6.23 3.74 4.6 3.64 6 18.8 1.72 2.23 1.15 3.96 5.79 302 284.36 268.76 302 302 5.952 2.156 1.724 1.379 1.666 <0.001 0.032 0.086 0.169 0.097 isolation at the p < 0.05 level. Given our moderate sample size, it is worth noting that rural older adults reported more help with ADL impairments, higher levels of loneliness, and greater social isolation at the p < 0.10 level of significance. Table 4 presents the hierarchical regression models used to test our remaining hypotheses. Our second set of hypotheses posited that after controlling for the effects of sociodemographic characteristics, measures of physical (Adj. R2 = 0.115, p < 0.001) and psychosocial (Adj. R2 = 0.191, p < 0.0001) well-being would be associated with life satisfaction. Data supported both hypotheses. In Model 2 (Adj. R2 = 0.115, p < 0.001), self-rated health (M = −0.56; SD = 0.16; p < 0.001) contributed to life satisfaction, and in model 3 (Adj. R2 = 0.19, p < 0.001), loneliness (M = −0.24; SD = 0.11; p < 0.03) and affect balance (M = 0.12; SD = 0.03; p < 0.001) added to the explained variance in life satisfaction. Lastly, the data supported our hypothesis that after controlling for the effects of sociodemographic characteristics, physical well-being, and psychosocial well-being, geographic locale (urban vs. rural) would be significantly associated with life satisfaction (Adj. R2 = 0.209, p < 0.006). frameworks on healthy-active aging. We will briefly discuss the findings on each set of variables in our multivariate models. This study furthers our understanding of determinants of life satisfaction among older adults in Mongolia and adds important information to international conversations about well-being indicators of human development, the positive psychology movement in later life, and policy Demographics Beyond the development of a country’s national economy, individual demographics [9], health and social-psychological factors [25], and living environments influence older adults’ assessments of life satisfaction [26]. In the current study, neither age, gender, nor number of adult children was related to life satisfaction, although living with grandchildren had a positive impact. Fertility rates have steadily declined in Mongolia, and the government encourages childbirth as a means to increase population growth. Rural older adults had more children on average than urban dwellers [27]. Caring for grandchildren can lead to happiness in the long run. Having more grandchildren, but not spending more time with them, increased life satisfaction [28]. Similarly, the SHARE cohort study of 13 European countries concluded that seeing their grandchildren significantly impacts older women’s life satisfaction [29]. Education is an investment that bears life-long benefits. Higher levels of education are associated with better health and mental health [30] and social participation [31]. We found that completion of vocational or higher education as compared to no formal education was related to greater life satisfaction. Rural older adults had lower levels of formal education than their urban counterparts due to post-transition educational Life Satisfaction among Older Adults in Rural and Urban Mongolia Biomed Hub 2023;8:79–87 DOI: 10.1159/000533917 Discussion 83 Downloaded from http://karger.com/bmh/article-pdf/8/1/79/4037876/000533917.pdf by guest on 27 October 2023 Dependent variable Life satisfaction Sociodemographics Age (range 55–88) Number of grandchildren in household Physical factors Self-rated health ADL impairments Psychosocial factors Social participation No. of adult children Loneliness Affect balance Social isolation Urban R2/Adj. R2 Biomed Hub 2023;8:79–87 DOI: 10.1159/000533917 Model 1 Model 2 Model 3 Model 4 0.105/0.077 0.147/0.115 0.233/0.191 0.253/0.209 sig.F.Change p < 0.000 p < 0.001 p < 0.0001 p < 0.006 predictor beta beta sig. beta 95% CI [LL, UL] Otgon/Burnette/Mukhtar/Casati/ Myagmarjav (Intercept) Age Sex = male Marital_new = double Edu_level = secondary Edu_level = high_school Edu_level = vocational Edu_level = bachelor_more Grandchildren in household Paid work Self-rated health ADL impairments Number of adult children Social participation Loneliness Affect balance Social isolation Living area = urban beta sig. beta 95% CI [LL, UL] beta sig. beta 95% CI [LL, UL] beta sig. 95% CI [LL, UL] 6.673** −0.006 0.453 −0.004 [4.294, 9.051] [−0.041, 0.03] [−0.12, 1.025] [−0.503, 0.495] <0.0001 0.748 0.121 0.987 8.328** −0.005 0.368 0.059 [5.819, 10.837] [−0.04, 0.03] [−0.194, 0.93] [−0.432, 0.549] <0.0001 0.78 0.199 0.814 7.265** −0.005 0.493 −0.065 [4.417, 10.114] [−0.04, 0.03] [−0.059, 1.044] [−0.544, 0.413] <0.0001 0.777 0.08 0.789 6.948** −0.007 0.523 −0.092 [4.123, 9.773] [−0.041, 0.027] [−0.023, 1.068] [−0.566, 0.381] <0.0001 0.691 0.06 0.702 0.535 [−0.262, 1.332] 0.188 0.383 [−0.402, 1.169] 0.338 0.393 [−0.363, 1.149] 0.307 0.243 [−0.512, 0.998] 0.527 0.944 [0.199, 1.688] 0.013 0.794* [0.058, 1.531] 0.035 0.772* [0.062, 1.482] 0.033 0.484 [−0.248, 1.215] 0.194 1.475** [0.65, 2.299] <0.0001 1.122** [0.294, 1.949] 0.008 1.126** [0.326, 1.927] 0.006 0.711 [−0.134, 1.556] 0.099 1.075** [0.317, 1.834] 0.006 0.911* [0.158, 1.663] 0.018 0.962** [0.229, 1.695] 0.01 0.49 [−0.309, 1.288] 0.229 0.28* 0.021 0.271* [0.039, 0.504] 0.022 0.285* [0.06, 0.51] 0.013 0.257* [0.034, 0.48] 0.024 0.007 0.707* [0.073, 1.34] 0.029 −0.554* [−0.867, −0.241] 0.001 −0.053 [−0.247, 0.141] 0.591 0.57 −0.348* 0.012 0.031 [−0.046, [−0.658, [−0.176, [−0.076, 0.07 0.028 0.898 0.567 0.583 −0.382* 0.045 0.033 [−0.026, [−0.689, [−0.143, [−0.073, 0.06 0.015 0.639 0.544 0.033 [−0.089, 0.154] 0.598 0.088 [−0.038, 0.215] 0.17 [−0.439, 0.003] [0.065, 0.171] [−0.006, 0.072] [0.214, 1.259] 0.053 <0.0001 0.098 0.006 [0.043, 0.518] 0.889** [0.25, 1.528] 1.185] −0.038] 0.201] 0.139] −0.241* [−0.464, −0.019] 0.034 −0.218 0.115** [0.062, 0.169] <0.0001 0.118** 0.025 [−0.014, 0.065] 0.204 0.033 0.737** *indicates p < 0.05. **indicates p < 0.01. Downloaded from http://karger.com/bmh/article-pdf/8/1/79/4037876/000533917.pdf by guest on 27 October 2023 84 Table 4. Multiple regression analysis for life satisfaction predictors 1.191] −0.074] 0.233] 0.139] inequality and semi-nomadic lifestyles [32]. However, the impact of education on life satisfaction was not as strong as living areas. Psychosocial Well-Being A wealth of evidence exists on the positive impact of social networks, social integration, and social participation on the life satisfaction of older adults [36]. In a dataset in the USA and Japan, friends and family relationships significantly affected the life satisfaction of older adults [37]. In our data, neither social participation nor social isolation was significantly associated with life satisfaction. Consistent with previous studies in, for example, China [38], Poland [39], and South Korea [40], greater loneliness reduced life satisfaction. Affect balance was also significantly associated with life satisfaction. Positive feelings predicted higher levels of satisfaction and vice versa. Whereas life satisfaction is a general assessment of one’s quality of life, affect balance is a more general assessment of angry, happy, and depressed feelings over the past few days. It is a dynamic process that strongly affects older adults’ life satisfaction, regardless of age, gender, education, or where they live [41]. To summarize, this study aimed to examine older adults’ assessment of life satisfaction in rural and urban Mongolia and to determine whether sociodemographic, physical health, and psychosocial characteristics were related to observed differences in the two groups. Consistent with previous research [42, 43], we found that life satisfaction was significantly lower for rural older adults. We suggest several possible reasons for this finding and recommendations for improvement. First, access to quality health and social services is far better in urban areas [44]. Second, Mongolia’s countryside is different from rural communities in more developed Western countries, with poor housing, low income, large families, and poor access to services [45]. For example, in Canada, England, and Life Satisfaction among Older Adults in Rural and Urban Mongolia Limitations This study has several limitations. Life satisfaction was measured by a single item rather than a multidimensional measure and may therefore be influenced by respondents’ mood during the interview. Seasonal effects might also influence the data collected during the winter season. Owing to our cross-sectional design and non-probability sampling strategy, we cannot make causal inferences about our findings or can we generalize our results to a larger population. Biomed Hub 2023;8:79–87 DOI: 10.1159/000533917 85 Downloaded from http://karger.com/bmh/article-pdf/8/1/79/4037876/000533917.pdf by guest on 27 October 2023 Physical Well-Being Previous studies confirm that self-rated health directly affects older adults’ life satisfaction [33] and that illness reduces satisfaction [34]. In the current study, older adults who rated their health as good reported better life satisfaction, regardless of demographic or psychosocial factors. With increased urbanization and social development, progress in economic and health equity is improving the health status of the population [35]. Therefore, to improve life satisfaction among the older adult population, the emphasis now must be on improving access to health services in rural areas. Eastern Europe, rural older adults report higher life satisfaction than urban ones [46]; yet, our findings are consistent with those of developing countries such as China [47]. The F-change scores in our hierarchical regression show that each step in the model added significantly to the variance in life satisfaction. It is therefore important to consider the overall contributions of sociodemographic characteristics, health and functional well-being, and psychosocial measures. Yet, even after controlling for the effects of these essential features of life satisfaction, living in a nonurban area was associated with lower levels of life satisfaction. Rural and remote areas in developing countries have more pronounced population aging than urban areas and thus tend to have a greater share of older adults. Lower population density and geographic dispersion make it more difficult and costly to develop comprehensive, sustainable service infrastructures [44]. There is thus a grave mismatch between the availability and accessibility of resources and the needs of older adults, who are more likely to experience diminished economic resources and opportunities, declining physical, functional, and cognitive health, reduced mobility, loss of social networks with internal rural-to-urban and cross-national migration, and harsh weather and degradation of the environment on which their livelihood depends. To address these needs, innovations in policies, programs, and practice should highlight both near- and longterm care to address the economic, health, and mental health needs of older adults in rural areas. Reducing educational inequalities and developing sustainable opportunities for generational and inter-generational economic and social engagement can also enhance older adults’ life satisfaction in more rural and remote areas. It may also be important to reconsider the current mandatory retirement ages for men and women and to systematically explore the needs and resources available to older adults by age group, gender, and geographic region. Acknowledgments Funding Sources We want to thank the geriatricians, senior associations’ staff, and health centers’ practitioners who helped recruit study participants. Publication of this work does not have a funding source. Author Contributions Statement of Ethics The Mongolian National University of Medical Sciences Ethics Review Committee approved this study (protocol 15: 32016-15). A written informed consent was obtained from participants. Saranchuluun Otgon collected the data, analyzed, interpreted the data, and drafted the manuscript. Denise Burnette designed the manuscript and revised interpretation. Yerkyebulan Mukhtar worked on analysis and data. Fabio Casati revised the manuscript. Sugarmaa Myagmarjav revised the manuscript and interpretation of the data. 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