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Literature Review: Relationship between Subjective Age and Health Outcomes

Info: 2409 words (10 pages) Nursing Literature Review
Published: 23rd Mar 2021

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Tagged: health

Literature Review: Relationship between Subjective Age and Health Outcomes

Aging is a complex process and is measured in terms of years and months a person has lived since birth; however, that does not always correlate with an individual’s self-perception of age. Subjective age is a multidimensional construct and is defined as a person’s independent feeling of being older or younger than their chronological age. Additionally, there is a discrepancy between younger and older adults, the gap between an individual’s chronological age and subjective age increases with their actual age (Kornadt et al., 2018, p. 768). In other words, as people grow older, the difference between their actual and preferred age gets much larger. Researchers often assess subjective age based on the number of years in relations to their actual age or simply inquiry the person about their subjective feelings about their age. According to Stephan et al. (2018), older adults felt about 8 to 12 years younger, while those that felt that they have aged reported feeling 8,11, and 13 years older (Stephan et al., 2018, p. 5). A predominant finding relating to subjective age is that those that feel younger have an advantage in health than those that feel older than their actual age (Kornadt et al., 2018, p. 768). Those advantages in health include increased longevity, decreased risk to diseases and disorders, and lower hospitalization rates (Stephan et al., 2018, p. 2). Contrarily, those that feel older than their age has a higher risk of mortality, lower level of physical function, and lower quality of life (Stephan et al., 2018, p. 5). There are other factors that may contribute to the disparity of the gap between a person’s self-perceived age and real age such as education, work, physical activity, and health status. Thus, these findings imply that the self-perception age of an individual is an indicator of age-related and health-related outcomes, beyond the scope of their chronological age. Subjective age should be considered as an extension rather than a substitute for chronological age, in which they are operationalized together. This extension has the potential to tell us more about the consequences of the aging process. The purpose of this paper is to analyze and explain the difference in subjective age compared to their real age between young and older adults.

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The empirical papers that will be analyzed are Galambos et al. (2015) research, subjective age and younger adult research, “Chronological and subjective age in emerging adulthood: The crossover effect. Journal of Adolescent Research” and Bergland et al. (2014) research, subjective age and older adults, “Predictors of subjective age in people aged 40–79 years: A five-year follow-up study. the impact of mastery, mental and physical health. Aging & Mental Health.” In Galambos et al. (2015) study, the aim of the research is to explore the relationship between chronological age and self-perceived age and its predictors in young adults (Galambos et al., 2015, p. 538). Whereas, in Bergland et al. (2014) research, the objective of the study is to measure subjective age and its changes and exploring factors that may predict the measurements amongst older adults (Bergland et al., 2015, p. 653).

There are available multiple approaches for choosing the right method for the research. Galambos et al. (2015) used a cross-sectional research approach (Galambos et al., 2015, p. 543). On the other hand, Bergland et al. (2014) used a longitudinal research that was followed up after five years in his study (Bergland et al., 2015, p. 653). Both research methods have their advantages and disadvantages, cross-sectional is suitable for investigating age differences; But it does not show age changes or age and cohort effects can not be differentiated (Harper & Dobbs, 2018, p. 30). Longitudinal studies are beneficial when looking at age changes and discriminating between age and cohort effects; Yet, age and time of measurement effects often cannot be separated (Harper & Dobbs, 2018, p. 32). For instance, cross-sectional may be inaccurate as results may not be generalizable to the entire population, and longitudinal comparisons may be biased if practice effects occur. Therefore, both study methods have its pros and cons which can influence the results of the data collected.

Methodologies explains the procedure used to investigate variables in a research. Galambos et al. (2015) used a questionnaire to assess self-perceived age as well as other variables (Galambos et al., 2015, p. 544). While, Bergland et al. (2014) determined subjective age by giving a score which was collected by subtracting a person’s real age from their felt age (Bergland et al., 2015, p. 654). Galambos et al. (2015) questionnaire to assess self-perceived age consisted of psychosocial maturity, number of role transitions, financial dependence, economic pressure, and alcohol use (Galambos et al., 2015, p. 544). While, Bergland et al. (2014) used telephoned interviews and questionnaires to determine subjective age by giving a score which was collected by subtracting a person’s real age from their felt age (Bergland et al., 2015, p. 654). Galambos et al. (2015) sample size included 190 university students majoring in psychology with 140 female students and 50 male students. Education and ethical diversity were taken into consideration, as most students were white and had various educational background. Students were offered a chance to sign up for the study in class and then attended group sessions during or outside of class. Those that partook in the study received an extra credit only if enrolled in an introductory psychology class (p. 544). Bergland et al. (2014) sample was originally made up of 8298, however only 2471 older adults with ages between 40 and 79 responded, participants were surveyed in 2002/2003 and 2007/2008. The sample demographics represented different geographic regions of Norway. Social characteristics and age cohorts of 10-year interval were also examined to predict outcomes. Researchers send out telephone interviews and postal questionnaires which was randomized according to age and sex (p. 655). Thus, in both studies, the cross-sectional design could have led to ungeneralizable results, while the longitudinal design may have a high attrition rate.

The measurement or psychological assessment were similar in both studies, however varied slightly in variables. Galambos et al. (2015) used a criteria measurement that were categorized into five sub-components to assess subjective age. Psychosocial maturity, which was measured with the use of the Erikson Psychosocial inventory scale. Role transition, which was measured through questions such as if they lived with their parents, if they are employed, or married with children. Financial dependence, two questions were asked which were if they were a dependent child and if their parents were financially providing for their school expenses. Economic pressure, participants were asked to numerically grade from one to four in regards to if they had enough money for certain scenarios. Finally, Alcohol use, participants were asked various questions about alcohol usage such as the amount of alcohol consumed in a week (p. 545). Whereas, Bergland et al. (2014) used a SF-12 questionnaire based on self-report and it was used as a tool to measure individual’s self-perception of their health status. It is separated into two components for this study which were physical and mental health, scores were ranged from 0 to 100 in both. The SF-12 is a shorter version of the SF-36 which has questions based on the two components such as how active an individual is during the week or if they experienced depressive moods recently respectively. Hence, both studies assessment measurement was quite similar, however Bergland et al. (2014) had a greater domain explored in regards to subjective age which could be more benefitable in determining extraneous or important variables.

The results and findings varied in each research study, they allow researchers to interpret the data in a comprehensive way and find patterns. Galambos et al. (2015) findings were similar to other studies, the average post-secondary student felt older than their chronological age (Galambos et al., 2015, p. 550). Variables that contributed to this finding is psychosocial maturity, most participants that responded to feeling older were associated to values such as independence, marriage, and career searching (Galambos et al., 2015, p. 551). Looking at Bergland et al. (2014) research results, in both terms the study was conducted, the sample size of older adults reported they felt younger than their chronological age (Bergland et al., 2015, p. 656). Factors that contribute to this result is the level of education or physical and mental status, most participants that felt younger were of lower education level and a good subjective mental or physical status (Bergland et al., 2015, p. 658).  Therefore, it can be stated that in both research studies, an individual’s subjective age increases accordingly to their chronological age.

In essence, younger adults felt slightly older than their chronological age while older adults felt significantly younger than their chronological age. The two research papers compliment each other as they measure subjective age across difference lifespans, starting from emerging adulthood to late adulthood. It can be seen that, young adults reported feeling younger due to psychological maturity which may be defined as the need to engage in mature behaviors. As individuals reach the older adult stages, they feel more youthful, which was physically and mentally depended on their self-described health status with education also being a factor.

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Bergland et al. (2014) research study provides stronger evidence to their results than Galambos et al. (2015) research study. Bergland et al. (2014) used a longitudinal study which had a much greater sample size and was randomized in terms of age and sex, so the results can be more generalizable (Bergland et al., 2015, p. 653). Also, compared to Galambos et al. (2015) research, there was not a huge discrepancy between genders, therefore the results were not biased towards a specific gender group and consequently skew the results (Bergland et al., 2015, p. 655). Moreover, researchers are able to follow developmental changes of a specific population over time at both group and individual levels. Therefore, the findings have a higher indicator of cause-and-effect relationships between variables than a cross-sectional design in regards to subjective age. Lastly, the large age range covered allows for a more comprehensive interpretation of the variability of age identity and different factors that contribute to each age group (Bergland et al., 2015, p. 659). Hence, Bergland et al. (2014) has stronger evidence due to interventions to decrease bias and increase generalizability in the data compared to Galambos et. (2015) research.

There were certain limitations in both studies that were acknowledged and mention.  Galambos et al. (2015) mention in their research conclusion that, the limitations of the study included the sample size, since undergraduate students do not reflect on the entire population of emerging adults. Also, there were more females than males as mentioned earlier, which can cause underlying factors related to gender differences. Lastly, the sample size was not ethically diverse thus will limit generalizability (Galambos et al., 2015, p. 552). While in Bergland et al. (2014) study, there was a slight difference between the two terms the study was conducted, participants were of course younger, had a better health status, and were more educated than those studied in the second term. Attrition is also another limitation as it can impact the generalizability of the results. Data was focused primarily on subjective findings rather than objective findings; therefore, it does not examine underlying factors that may contribute to the data such as functional capacity or social participation. Lastly, the sample size of age differed slightly across age groups which may alter the results and generalizability (Bergland et al., 2015, p. 659).

Overall, subjective age needs to be explored in future studies to interpret a more comprehensive understand of the relationship between subjective health and future health outcomes. According to the research papers examined, it can be implied that subjective age in relations to chronological age can be used as an indicator of health-related outcomes and mortality in the aging process. Future studies should examine subjective age in relations to the individual’s health status in various stages of life to determine if it can be seen as a predictor such as that it will lead to increase longevity or a decrease risk for death or disease.

References

  • Bergland, A., Nicolaisen, M., & Thorsen, K. (2014). Predictors of subjective age in people aged 40–79 years: A five-year follow-up study. The impact of mastery, mental and physical health. Aging & Mental Health, 18(5), 653-661. doi:10.1080/13607863.2013.869545
  • Galambos, N., Turner, P., & Tilton-Weaver, L. (2005). Chronological and subjective age in emerging adulthood: The crossover effect. Journal of Adolescent Research, 20(5), 538-556. doi:10.1177/0743558405274876
  • Harper, L., & Dobbs, B. (2018). Adult development And Aging: The Canadian Experience (1st ed.). Nelson Education Ltd.
  • Kornadt, A. E., Hess, T. M., Voss, P., & Rothermund, K. (2018). Subjective age across the life span: A differentiated, longitudinal approach. The Journals of Gerontology: Series B, 73(5), 767-777. doi:10.1093/geronb/gbw072
  • Stephan, Y., Sutin, A. R., & Terracciano, A. (2018). Subjective age and mortality in three longitudinal samples. Psychosomatic Medicine, 80(7), 659-664. doi:10.1097/PSY.0000000000000613

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