Skip to main content
Download PDF

Subjective social status and socio-demographic correlates of perceived discrimination among older adults in India

BMC Geriatrics volume 24, Article number: 617 (2024) Cite this article

Abstract

Background

Considering India’s diversity, marked by differences in caste, class, ethnicity, religion, region, and language, discrimination can take on varying forms across social-structural locations. We examined the association between subjective social status (SSS) and perceived discrimination, and assessed the sociodemographic correlates of perceived discrimination among older persons in India.

Methods

Data come from the 2017-18 wave 1 of the Longitudinal Aging Study in India (LASI) with a sample of 30,253 adults 60 years or older. SSS was examined using the Macarthur scale with a ladder technique. Perceived discrimination was evaluated with the Everyday Discrimination Scale. Multivariable logistic regression models examined the odds of reporting discrimination by its types and attributions.

Results

39% of older adults reported low SSS, whereas 7.3% reported high SSS. Older adults with low SSS had significantly higher odds of experiencing some discrimination than those with high SSS. Compared to high-SSS peers, low-SSS individuals attributed age, gender, caste, financial, and health status as reasons for discrimination. Older women attributed gender as a reason for discrimination. Caste was reported as a reason for discrimination by rural but not urban dwellers. Relative to northerners, those from southern India reported age, financial, and health statuses as reasons for discrimination.

Conclusions

That low-SSS older adults reported age, gender, caste, financial status, and health status as reasons for discrimination and that this association persisted after considering objective indicators of socioeconomic status (SES) is suggestive of SSS as independently consequential for perceived discrimination. These findings are useful for care providers and practitioners as they encourage older patients -- especially those with low SSS who may feel stigmatized -- to seek care, comply with care regimen, and engage in behaviors that protect and promote health.

Peer Review reports

Background

Perceived discrimination is the perception of prejudice or unjust treatment based on personal attributes, such as age, gender, race, social class, caste, religion, disability, and physical appearance [1, 2]. Perceived discrimination can discourage or make it more cumbersome for individuals to access essential services, spaces, and institutions [3,4,5,6]. Individuals who experience discrimination report a weakened sense of self [7], worsened health behaviors [1], increased rates of mental distress [2, 8], and chronic disease [9, 10], including cardiovascular [11, 12] and cognitive impairments [2, 13]. Determining what renders older adults susceptible to discrimination is vital to producing policies and programs that protect them from adverse health outcomes.

Most studies on discrimination have delved into unjust treatment endured by racial and ethnic minorities in the US. Studies in developed nations also have investigated discrimination based on gender [14], sexual orientation [15, 16], and disability [17]. Further, we know the harmful effects of lower SES on self-appraised discrimination [18,19,20,21], and given their significance in India, researchers are studying caste and religion based discriminatory practices [22, 23]. Despite the expanding literature on the correlates and consequences of discrimination, we are aware of no study that has assessed, in India, how perceptions of everyday discrimination in later life vary based on SSS.

SSS, a measure of one’s own position relative to others in society [24], often proves to be a more influential factor in predicting health than the objective measures of SES, including education, occupation, income, wealth, and caste [25,26,27,28]. Aside from financial scarcities, SSS captures people’s feelings about the often “unquantifiable” social and psychological facets of SES, including power, prestige, mainstream social connections, perceived justness, and status embodiment [26, 29,30,31]. In evaluating SSS, individuals weigh their socioeconomic resources and consider the value attached to such resources (e.g., quality of one’s education and the returns to education) and other understated everyday life experiences, including the quality of social interactions [32]. SSS may be a more effective marker of perceived discrimination than SES, given that appraising one’s social standing compared to others may capture experiences related to financial status and other social statuses, including age, gender, caste, religion, health, and disability.

People who consider themselves as occupying lower positions within the social hierarchy may be more aware of or predisposed to recognize instances of prejudice. Given that low SSS is related to anxiety, depression [33, 34] and increased hopelessness and passivity [35, 36], individuals with low SSS may be more vigilant towards discriminatory experiences [37], including micro-aggressions. Compared to high-SSS individuals, low-SSS persons also withstand more harmful life events [38], including loss of employment, housing, and health care. Such adversities may be ascribed to discrimination [39]. Relatedly, compared to high-SSS peers who enjoy greater self-efficacy, low-SSS persons report feeling far less self-efficacious [40, 41] and view adverse life experiences as caused by external social circumstances, including social inequity [40,41,42].

Although SSS and perceived discrimination have garnered attention in low and middle-income countries (LMICs), including India, researchers have yet to investigate the link between the two in India. With the benefit of discerning subjectivity to understand how “external realities of SES are internalized” [43 p.2], SSS may be a stronger correlate than SES of several outcomes of interest. This likely is for the same reason why relative income or perceived income disparity often emerge as more reliable barometers of health than absolute income and wealth [43,44,45,46]. In prior work, when SES and SSS were both considered, SSS, rather than SES, remained linked with several major outcomes of health, including depression, cardiovascular disease, self-rated health, epigenetic aging, and mortality [24,25,26, 29, 31, 47, 48]. We expect that this pattern of relationships will recur with the outcome of perceived discrimination.

Therefore, we examine the relevance of SSS for perceived discrimination after considering objective SES among older individuals in India, and also assess the sociodemographic correlates of perceived discrimination among older Indians. This work is important given that neither studies on SSS nor discrimination are focused on older Indians, the increasing aging Indian population, and the broadening social and economic inequities in India [49, 50]. Assessing the relevance of SSS for perceived discrimination may be particularly consequential in later life as older adults who internalize negative attitudes are more susceptible to physical [51], mental [52], and cognitive distress [53]. Considering India’s diversity, marked by differences in caste, class, ethnicity, religion, region, and language, discrimination can take on varying forms across social-structural locations. Understanding these nuances is important for crafting guided interventions and policies that tend to the specific needs and challenges endured by people of diverse social backgrounds. Therefore, we also examine the associations between SSS and other sociodemographic factors and the reasons for perceived discrimination in older Indians.

Methods

Data

Data come from the 2017-18 wave 1 of the Longitudinal Ageing Study in India (LASI) with a sample of 73,396 adults aged 45 and above and their spouses regardless of age across all states and union territories of India. With a three-stage sample design in rural regions and a four-stage sampling design in urban areas, the LASI survey used a multistage stratified area probability cluster sampling design. The survey report included detailed methodology, including complete information on the survey’s design and data collection [54]. The survey design, instruments, and protocols are harmonized with the Health and Retirement Study (HRS) and its sister studies worldwide [55]. The survey collected data from 31,464 older adults aged 60 years and above. Upon omitting the cases with missing items, the study’s final sample includes 30,253 older Indians.

Subjective social status

SSS was examined using the Macarthur scale [56] with a ladder technique, and the specific question used to assess SSS was, “Think of the ladder with 10 stairs as representing where people stand in our society. At the top of the ladder are the people who are best off – those who have the most money, the most education, and the best jobs. At the bottom are the people who are the worst off – those who have the least money, least education, and the worst jobs or no jobs. The higher up you are on this ladder, the closer you are to the people at the very top, and the lower you are, the closer you are to the people at the very bottom of your society” [54]. Respondents were directed to: “Please indicate the number given on the rung on the ladder where you would place yourself.” A score of 1–10 was generated per the number of rungs marked by the respondents. A score of 8–10 was considered “high,” 4–7 “middle,” and 1–3 “low.”

Everyday discrimination

Everyday discrimination taps into routine and relatively minor experiences of mistreatment and was assessed using the shorter version of the Everyday Discrimination Scale [57]. The LASI asked participants how often any of the following events have happened to them in their daily life: (i) “You are treated with less courtesy or respect than other people”; (ii) “You receive poorer service than other people at restaurants or stores”; (iii) “People act as if they think you are not smart”; (iv) “People act as if they are afraid of you”; (v) “You are threatened or harassed” and (iv) “Receive poorer service or treatment than other people from doctors or hospitals” (Cronbach’s alpha = 0.84). The six-point response scale to each item ranges from “never” to “almost every day.” Those reporting experiences of any of the above items at least once a month were classified into “yes” and otherwise “no,” representing experiences of perceived discrimination. Respondents also were asked what they believe are the reasons for these experiences. The reasons include age, gender, religion, caste, financial status, health conditions (body weight, physical disability, and other aspects of health), and others.

Covariates

Given prior studies linking perceived discrimination to multiple sociodemographic characteristics [17, 58,59,60], we adjusted for several conceptually relevant covariates. We included age (60–69 years, 70–79 years, and 80 + years); sex (male and female); marital status (married, widowed, and others); living arrangements (living alone, with spouse, with spouse and children and other living arrangements), work status (never worked, currently not working, currently working and retired), household monthly per capita consumption expenditure quintiles (poorest, poor, middle, rich, and richest); caste (scheduled caste, scheduled tribe, other backward classes, and general); place of residence (rural and urban); and geographic regions (north, central, east, northeast, south, and west).

Statistical analysis

We report descriptive statistics of the total sample and subsamples by different SSS groups. We further present the weighted estimates from cross-tabulations of types of perceived discrimination by SSS and other sociodemographic characteristics. Multivariable logistic regression models were employed to assess the odds of reporting discrimination by its types and the reasons after controlling for the selected covariates. Separate multivariate logistic regression analyses were conducted for the different types and reasons. We report the adjusted odds ratios (AOR) and confidence intervals (CI) from the estimates. Multivariable analyses were also weighted to consider the stratified sampling and to provide the national estimates. Regression diagnostics were used to rule out any potential regression assumptions violation. The statistical analysis was conducted using Stata 15.1.

Results

Table 1 presents the socioeconomic and demographic profile of older Indians in the study. A higher percentage of the sample was women (52.8% vs. 47.2%). 11% of the respondents were aged 80 years or older. More than half (56.4%) had no formal education. 36% were widowed, and 5.7% lived alone. More than 30% were currently working, and 7.3% were retired. A total of 39.1% of older Indians reported a low SSS and only 7.3% reported a high SSS.

Table 1 Descriptive statistics
Full size table

Table 2 presents the prevalence of perceived discrimination among older adults by types of discrimination. More than 5% of the respondents experienced treatment from people with less courtesy, around 2% received poor service at restaurants or shops, reported other people’s thoughts about them as not smart (2.3%) or afraid of (1.9%), 2% were threatened or harassed, and 1.6% received poor service at healthcare facilities. Overall, 7.7% of older Indians reported at least some type of discrimination. Notably, the bivariate associations between the independent variables and the outcome were similar to the multivariable, adjusted models.

Table 2 Prevalence of perceived discrimination (n = 30,253)
Full size table

Table 3 presents the multivariable estimates of perceived discrimination by its types among older adults. Older Indians with a low SSS had significantly higher odds of experiencing some type of discrimination (AOR: 3.00, CI: 1.77–5.10) than the referent group with a high SSS. People who belonged to the general category (mostly higher castes) reported lower odds of discrimination (AOR; 0.80, CI: 0.64- 1.00) than those in the referent SC group. Older adults from the eastern (AOR: 0.35, CI: 0.28–0.44) and north eastern regions (AOR: 0.37, CI: 0.26–0.53) reported lower odds of discrimination than the referent group from the northern region of India.

Table 3 Logistic regression estimates of perceived discrimination by types (n = 30,253)
Full size table

Table 4 provides the multivariable estimates of reasons for perceived discrimination among older adults. Older adults with a low SSS reported age (AOR: 1.40, CI: 1.09–1.81), gender (AOR: 8.28, CI: 2.46–27.9), caste (AOR: 2.45, CI: 1.23–4.90), financial status (AOR: 5.21, CI: 3.23–8.40) and health status (AOR: 1.90, CI: 1.00- 3.60) as reasons for discrimination than the referent group with a high SSS. Older women reported gender as a significant reason for perceived discrimination (AOR: 4.57, CI: 2.79–7.49) than the referent male group. Muslims in India reported religion as a significant reason for discrimination (AOR: 4.28, CI: 2.61–7.01) than the referent group of Hindus. Lower odds of reporting caste as a reason for perceived discrimination were observed among the general category (AOR: 0.30, CI: 0.19–0.48) than those referent group who belonged to SC. Caste was reported as a significant reason for discrimination primarily by rural residents (AOR: 2.00, CI: 1.34–2.98) than their referent urban peers. Older adults from the southern region reported age (AOR: 1.21, CI: 1.00- 1.46), financial status (AOR: 1.82, CI: 1.40–2.36), and health status (AOR: 1.99, CI: 1.26–3.14) as reasons for discrimination than their referent peers from the northern region.

Table 4 Logistic regression estimates of perceived reasons for discrimination (n = 4,600)
Full size table

Discussion

The purpose of this study was to examine whether SSS and various sociodemographic factors relate to perceptions of everyday discrimination among older persons in India. Our findings indicate that compared to counterparts in high-income nations, older Indians report a lower prevalence of perceived discrimination [13, 61]. We also observed that, unlike high-SSS peers, older adults with low SSS reported age, gender, caste, financial status, and health status as reasons for discrimination. Aside from SSS, caste, gender, and regionality also were found to be significantly linked with discrimination perceived by older Indians. Below, we discuss these findings and their implications for practice and policy.

The relatively lower prevalence of discrimination among older Indians in this study (7.7%) may be attributed to several factors. Given the enduring social, economic, and cultural inequities in India [49, 50], some may interpret and accept discrimination as normative [22, 62] and avoid reporting it. This may reflect “learned helplessness,” where people believe that their lives and what happens to them is beyond their control [22, 62]. Being unaware of discriminatory practices (e.g., unable to get hired or promoted because of social class) may also explain the lower prevalence of discrimination [22]. Alternatively, the lower prevalence of perceived discrimination in our study may reflect the reverence for older adults in Indian society, especially when accorded with the household headship [63, 64].

While overall rates of discrimination are lower among older Indians, certain segments of the population reported higher levels of perceived discrimation. Notably, even after accounting for SES, older adults with low SSS perceived instances of discrimination based on age, gender, caste, financial status, and health status. These findings may reflect the heightened vulnerability to stigma and social exclusion among individuals facing challenges, such as poor health, older age, gender disparities, and lower social caste and class backgrounds [20, 22, 60, 65,66,67,68]. Such challenges can be a source of low SSS, which we find associated with discrimination among older Indians. Our finding here also suggests that although objective indicators of SES may serve as reasonable proxies for life’s stressful experiences, SSS may capture the often inconspicuous aspects of older adults’ experiences within their communities. Though SSS and SES are closely related, presuming that SSS and SES are interchangeable could hide the unique short and longer-term dangers older adults endure. Given this, wellness screenings and psychological assessments administered at clinics and hospitals should incorporate SSS.

Aside from SSS, we found additional correlates of perceived discrimination. Caste was reported as a significant reason for discrimination by rural but not urban residents. This reflects research showing that urban Indians, especially the educated, are more inclined to welcome and socialize with neighbors from lower castes [68]. Urban environments, driven by meritocracy, competition, and productivity may dilute the influence of caste compared to rural areas [68,69,70,71]. Older women, not men, reported gender as a source for discrimination, reflecting gender inequality in India [72,73,74]. Older Indian women continue to assume secondary social status [67, 75,76,77,78], often forced into unpaid labor and faced with disparities in pension security and decision-making power over family finances [73]. Older women’s health and legal rights are often overlooked due to gender bias [79]. Such disparities may lead older women, not men, to attribute their experience of discrimination to gender. Further, older adults from the southern, not northern, regions of India reported age, financial status, and health status as causes for discrimination. The regional disparities in perceived discrimination may stem from the fact that southern Indian states, like Kerala, outperform the rest of the country in education and economic opportunities [80]. This could imply that older adults in the southern states are more aware of discrimination, and the relatively affluent older population in these regions may also be more inclined to report instances of it [81].

Limitations and future directions

Our study is limited in important ways. First, although, our study is the first within the Indian context to examine the relevance of SSS for perceived discrimination among older adults, the cross-sectional data in our study restrict us from making any cause and effect or temporal claims between SSS and perceived discrimination. Richards et al. [82], in their longitudinal study, discovered that although higher status is correlated with better health, within-individual analysis over time reveals no statistically consequential relationship between status and health. As such, forthcoming waves of LASI data would allow researchers to track individuals over time, observe how changes in SSS correspond to changes in perceived discrimination, and vice versa. Findings based on longitudinal data will also be useful for early intervention techniques, predictive modeling to anticipate future results, and trajectory analysis to discover different patterns of change. Second, considering that the same cognitive processes may be responsible in appraising one’s social status and recognizing instances of discrimination, errors in measuring either concept separately can occur, potentially rendering spurious correlations between SSS and perceived discrimination. The findings, as such, should be interpreted with caution. Future studies may consider objective measurement of discrimination that would require field experiments or audit studies or implicit bias tests.

Third, the Everyday Discrimination Scale [83] was designed to gauge the everyday experiences of ill-treatment faced by Black Americans [84]. This scale may not reflect, to its fullest, the forms of inequity endured by older Indians. This scale also does not measure major “lifetime” discrimination, health outcomes of which vary from those triggered by everyday instances of discrimination [58]. Fourth, while we accounted for several objective indicators of SES, such as household economic status and older adults’ education, there may be other important factors (e.g., income stability, wealth, or fiscal resources individuals may gain from close kin) that were not measured but could still influence individuals’ experiences of discrimination. As such, the direction and extent of bias introduced by these unmeasured aspects of SES remain unclear, and future research should strive to capture a more comprehensive assessment of objective SES to better understand its interplay with SSS and discrimination.

Lastly, because most humans simultaneously occupy more than one marginalized status, they may be simultaneously judged for multiple statuses. For instance, the association between gender and discrimination is likely more or less pronounced based on an older adult’s caste, and this could be because lower-caste women in India endure more serious health challenges than their higher-caste counterparts. The combination of gender and caste could be even more daunting if we add the place of residence to the equation. Lower-caste women in rural areas are more socioeconomically disadvantaged than their urban-dwelling peers [22]. Those with multiple stigmatized identities may likely report heightened levels of perceived discrimination. Alternatively, people facing multiple stigmas may be better equipped to cope with multiple stressors [85] because of a more evolved self-identity owing to adaptation and resilience [86, 87]. Future research to replicate our work among older Indians should consider these possibilities.

Notwithstanding the limitations, this study contributes to research on aging and discrimination. This is an important contribution given that research on perceived discrimination among older adults, compared to their younger peers, is limited in India. This is the first study to explore the the association of SSS with perceived discrimination among older Indians. We accomplish this by employing a substantial and heterogeneous sample of a nationally representative aging population, in contrast to prior works that measured discrimination prevalence in homogeneous samples or among individuals of any one social group, frequently reducing the generalizability of findings.

Conclusions

That older adults with low SSS reported age, gender, caste, financial status, and health status as reasons for perceived discrimination and that this association persisted even after considering objective indicators of SES is suggestive of SSS as a more effective marker of perceived discrimination than SES. Moreover, SSS, as a way of evaluating one’s social standing compared to others in society, may capture experiences related to not only financial status but also other social statuses, including age, gender, caste, religion, and health. These findings are useful for health care providers and practitioners as they encourage older patients -- especially those with low SSS who may feel stigmatized -- to seek care, comply with care regimen, and engage in behaviors that protect and promote health.

Data availability

The data are available at the Gateway to Global Aging Data (www.g2aging.org) and at the International Institute for Population Sciences (www.iipsindia.ac.in/content/LASI-data).

References

  1. Pascoe EA, Richman LS. Perceived discrimination and health: a Meta-Analytic Review. Psychol Bull. 2009;135:531–54.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Pengpid S, Peltzer K. Perceived discrimination and health outcomes among middle-aged and older adults in India: results of a national survey in 2017–2018. BMC Geriatr. 2021;21:559.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Benjamins MR. Race/ethnic discrimination and preventive service utilization in a sample of whites, blacks, mexicans, and Puerto ricans. Med Care. 2012;50:870–6.

    Article  PubMed  Google Scholar 

  4. Henderson C, Evans-Lacko S, Thornicroft G. Mental Illness Stigma, help seeking, and Public Health Programs. Am J Public Health. 2013;103:777–80.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Jacobs EA, Rathouz PJ, Karavolos K, Everson-Rose SA, Janssen I, Kravitz HM, et al. Perceived discrimination is Associated with reduced breast and cervical Cancer screening: the study of women’s Health across the Nation (SWAN). J Womens Health. 2014;23:138–45.

    Article  Google Scholar 

  6. Mirza SA, Rooney C. Discrimination prevents LGBTQ people from accessing health care. Cent Am Prog. 2018;18.

  7. Berjot S, Gillet N. Stress and coping with discrimination and stigmatization. Front Psychol. 2011;2.

  8. Williams DR, Neighbors HW, Jackson JS. Racial/Ethnic Discrimination and Health: findings from Community studies. Am J Public Health. 2003;93:200–8.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Sutin AR, Stephan Y, Carretta H, Terracciano A. Perceived discrimination and physical, cognitive, and Emotional Health in older Adulthood. Am J Geriatr Psychiatry off J Am Assoc Geriatr Psychiatry. 2015;23:171–9.

    Article  Google Scholar 

  10. Williams DR, Mohammed SA. Racism and health I: pathways and scientific evidence. Am Behav Sci. 2013;57. https://doi.org/10.1177/0002764213487340

  11. Dunlay SM, Lippmann SJ, Greiner MA, O’Brien EC, Chamberlain AM, Mentz RJ et al. Perceived Discrimination and Cardiovascular Outcomes in Older African Americans: Insights from the Jackson Heart Study. Mayo Clin Proc. 2017;92:699–709.

  12. Panza GA, Puhl RM, Taylor BA, Zaleski AL, Livingston J, Pescatello LS. Links between discrimination and cardiovascular health among socially stigmatized groups: a systematic review. PLoS ONE. 2019;14:e0217623.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Shankar A, Hinds P. Perceived discrimination: associations with physical and cognitive function in older adults. Health Psychol. 2017;36:1126–34.

    Article  PubMed  Google Scholar 

  14. Tabler J, Schmitz RM, Nagata JM, Geist C. Self-perceived gender expression, discrimination, and mental health disparities in adulthood. SSM - Ment Health. 2021;1:100020.

    Article  Google Scholar 

  15. Ayhan CHB, Bilgin H, Uluman OT, Sukut O, Yilmaz S, Buzlu S. A systematic review of the discrimination against sexual and gender minority in Health Care settings. Int J Health Serv. 2020;50:44–61.

    Article  PubMed  Google Scholar 

  16. Casey LS, Reisner SL, Findling MG, Blendon RJ, Benson JM, Sayde JM, et al. Discrimination in the United States: experiences of lesbian, gay, bisexual, transgender, and Queer americans. Health Serv Res. 2019;54:1454–66.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Rogers SE, Thrasher AD, Miao Y, Boscardin WJ, Smith AK. Discrimination in Healthcare Settings is Associated with disability in older adults: Health and Retirement Study, 2008–2012. J Gen Intern Med. 2015;30:1413–20.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Fuller-Rowell TE, Curtis DS, Chae DH, Ryff CD. Longitudinal health consequences of socioeconomic disadvantage: examining perceived discrimination as a mediator. Health Psychol. 2018;37:491–500.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Jokela M, Fuller-Rowell TE. Changing associations between socioeconomic status and self-reported discrimination from the 1990s to the 2010s in the United States. Int J Psychol. 2022;57:760–5.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Khatry P, Manokara K, Harris LT. Socioeconomic status and dehumanization in India: Elaboration of the Stereotype Content Model in a non-WEIRD sample. Soc Psychol Personal Sci. 2021;12:908–19.

    Article  Google Scholar 

  21. Lott B. Cognitive and behavioral distancing from the poor. Am Psychol. 2002;57:100–10.

    Article  PubMed  Google Scholar 

  22. Khubchandani J, Soni A, Fahey N, Raithatha N, Prabhakaran A, Byatt N, et al. Caste matters: Perceived discrimination among women in rural India. Arch Womens Ment Health. 2018;21:163–70.

    Article  PubMed  Google Scholar 

  23. Chalam KS. Caste-based reservations and human development in India. Los Angeles, Calif: Sage; 2007.

    Google Scholar 

  24. Adler NE, Epel ES, Castellazzo G, Ickovics JR. Relationship of subjective and objective social status with psychological and physiological functioning: preliminary data in healthy white women. Health Psychol off J Div Health Psychol Am Psychol Assoc. 2000;19:586–92.

    CAS  Google Scholar 

  25. Zell E, Strickhouser JE, Krizan Z. Subjective social status and health: a meta-analysis of community and society ladders. Health Psychol off J Div Health Psychol Am Psychol Assoc. 2018;37:979–87.

    Google Scholar 

  26. Singh-Manoux A, Marmot MG, Adler NE. Does subjective social status predict health and change in health status better than objective status? Psychosom Med. 2005;67:855–61.

    Article  PubMed  Google Scholar 

  27. Cundiff JM, Matthews KA. Is subjective social status a unique correlate of physical health? A meta-analysis. Health Psychol off J Div Health Psychol Am Psychol Assoc. 2017;36:1109–25.

    Google Scholar 

  28. Srivastava S, Muhammad T. Socioeconomic vulnerability and frailty among community-dwelling older adults: cross-sectional findings from longitudinal aging study in India, 2017–18. BMC Geriatr. 2022;22:201.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Adler N, Singh-Manoux A, Schwartz J, Stewart J, Matthews K, Marmot MG. Social status and health: a comparison of British civil servants in Whitehall-II with European- and african-americans in CARDIA. Soc Sci Med 1982. 2008;66:1034–45.

    Google Scholar 

  30. Anderson C, Kraus MW, Galinsky AD, Keltner D. The local-ladder effect: social status and subjective well-being. Psychol Sci. 2012;23:764–71.

    Article  PubMed  Google Scholar 

  31. Demakakos P, Nazroo J, Breeze E, Marmot M. Socioeconomic status and health: the role of subjective social status. Soc Sci Med 1982. 2008;67:330–40.

    Google Scholar 

  32. Adler NE. Health disparities through a psychological lens. Am Psychol. 2009;64:663–73.

    Article  PubMed  Google Scholar 

  33. Hoebel J, Maske UE, Zeeb H, Lampert T. Social inequalities and depressive symptoms in adults: the role of objective and subjective socioeconomic status. PLoS ONE. 2017;12:1–18.

    Article  Google Scholar 

  34. O’Leary D, Uysal A, Rehkopf DH, Gross JJ. Subjective social status and physical health: the role of negative affect and reappraisal. Soc Sci Med. 2021;291:114272.

    Article  PubMed  Google Scholar 

  35. Düren R, Yalçın Ö. How does subjective social status affect internalizing and externalizing problems among Syrian refugee adolescents? Curr Psychol. 2022. https://doi.org/10.1007/s12144-022-03002-4

    Article  Google Scholar 

  36. Kim J-H, Park E-C. Impact of socioeconomic status and subjective social class on overall and health-related quality of life. BMC Public Health. 2015;15:1–15.

    Article  Google Scholar 

  37. Hicken MT, Lee H, Ailshire J, Burgard SA, Williams DR. Every shut eye, ain’t sleep: the role of racism-related vigilance in racial/ethnic disparities in sleep difficulty. Race Soc Probl. 2013;5:100–12.

    Article  PubMed  PubMed Central  Google Scholar 

  38. McLeod JD, Kessler RC. Socioeconomic status differences in vulnerability to undesirable life events. J Health Soc Behav. 1990;31:162–72.

    Article  CAS  PubMed  Google Scholar 

  39. Muhammad T, Pai M. Association between subjective social status and physical frailty in older adults in India: perceived discrimination and III-treatment as mediators and moderators. Aging Clin Exp Res. 2023. https://doi.org/10.1007/s40520-023-02531-7

    Article  PubMed  Google Scholar 

  40. Kraus MW, Piff PK, Keltner D. Social class, sense of control, and social explanation. J Pers Soc Psychol. 2009;97:992–1004.

    Article  PubMed  Google Scholar 

  41. Kraus MW, Tan JJX, Tannenbaum MB. The Social Ladder: a Rank-based perspective on Social Class. Psychol Inq. 2013;24:81–96.

    Article  Google Scholar 

  42. Manstead ASR. The psychology of social class: how socioeconomic status impacts thought, feelings, and behaviour. Br J Soc Psychol. 2018;57:267–91.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Amir D, Valeggia C, Srinivasan M, Sugiyama LS, Dunham Y. Measuring subjective social status in children of diverse societies. PLoS ONE. 2019;14:e0226550.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Ball R, Chernova K. Absolute income, relative income, and happiness. Soc Indic Res. 2008;88:497–529.

    Article  Google Scholar 

  45. Daly M, Boyce C, Wood A. A social rank explanation of how money influences health. Health Psychol off J Div Health Psychol Am Psychol Assoc. 2015;34:222–30.

    Google Scholar 

  46. Wilkinson RG. The impact of Inequality. Soc Res. 2006;73:711–32.

    Article  Google Scholar 

  47. Ghaed SG, Gallo LC. Subjective social status, objective socioeconomic status, and cardiovascular risk in women. Health Psychol off J Div Health Psychol Am Psychol Assoc. 2007;26:668–74.

    Google Scholar 

  48. Hamlat EJ, Adler NE, Laraia B, Surachman A, Lu AT, Zhang J, et al. Association of subjective social status with epigenetic aging among black and white women. Psychoneuroendocrinology. 2022;141:105748.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Anand I, Thampi A. The Crisis of Extreme Inequality in India. Indian J Labour Econ. 2021;64:663–83.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Assouad L, Chancel L, Morgan M. Extreme Inequality: Evidence from Brazil, India, the Middle East, and South Africa. In: AEA Papers and Proceedings. American Economic Association 2014 Broadway, Suite 305, Nashville, TN 37203; 2018. pp. 119–23.

  51. Levy BR, Slade MD, Murphy TE, Gill TM. Association between positive age stereotypes and recovery from disability in older persons. JAMA. 2012;308:1972–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Allen JO, Solway E, Kirch M, Singer D, Kullgren JT, Moïse V, et al. Experiences of Everyday Ageism and the health of older US adults. JAMA Netw Open. 2022;5:e2217240.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Levy BR, Zonderman AB, Slade MD, Ferrucci L. Memory shaped by age stereotypes over time. J Gerontol B Psychol Sci Soc Sci. 2012;67:432–6.

    Article  PubMed  Google Scholar 

  54. International Institute for Population Sciences (IIPS), NPHCE. MoHFW HTHCS of PH (HSPH) and the U of SC (USC). Longitudinal ageing study in India (LASI) Wave 1, 2017-18, India Report. Mumbai.; 2020.

  55. Bloom DE, Sekher TV, Lee J. Longitudinal aging study in India (LASI): new data resources for addressing aging in India. Nat Aging. 2021;1:1070–2.

    Article  PubMed  Google Scholar 

  56. Adler NE, Epel ES, Castellazzo G, Ickovics JR. Relationship of subjective and objective social status with psychological and physiological functioning: preliminary data in healthy, white women. Health Psychol. 2000;19:586.

    Article  CAS  PubMed  Google Scholar 

  57. Shariff-Marco S, Breen N, Landrine H, Reeve BB, Krieger N, Gee GC, et al. MEASURING EVERYDAY RACIAL/ETHNIC DISCRIMINATION IN HEALTH SURVEYS: how best to ask the questions, in one or two stages, across multiple racial/ethnic groups? 1. Bois Rev Soc Sci Res Race. 2011;8:159–77.

    Article  Google Scholar 

  58. Ayalon L, Gum AM. The relationships between major lifetime discrimination, everyday discrimination, and mental health in three racial and ethnic groups of older adults. Aging Ment Health. 2011;15:587–94.

    Article  PubMed  Google Scholar 

  59. Luo Y, Xu J, Granberg E, Wentworth WM. A longitudinal study of Social Status, Perceived discrimination, and physical and emotional health among older adults. Res Aging. 2012;34:275–301.

    Article  Google Scholar 

  60. Maurya P, Sharma P, Muhammad T. Prevalence and correlates of perceived age-related discrimination among older adults in India. BMC Public Health. 2022;22:1–10.

    Article  Google Scholar 

  61. Kessler RC, Mickelson KD, Williams DR. The prevalence, distribution, and Mental Health correlates of Perceived discrimination in the United States. J Health Soc Behav. 1999;40:208–30.

    Article  CAS  PubMed  Google Scholar 

  62. Abramson LY, Seligman ME, Teasdale JD. Learned helplessness in humans: critique and reformulation. J Abnorm Psychol. 1978;87:49–74.

    Article  CAS  PubMed  Google Scholar 

  63. Srivastava S, Singh SK, Kumar M, Muhammad T. Distinguishing between household headship with and without power and its association with subjective well-being among older adults: an analytical cross-sectional study in India. BMC Geriatr. 2021;21:1–13.

    Article  Google Scholar 

  64. Srivastava S, Muhammad T, Sulaiman KM, Kumar M, Singh SK. Types of household headship and associated life satisfaction among older adults in India: findings from LASI survey, 2017–18. BMC Geriatr. 2022;22:78.

  65. Borooah V. Inequality in Health outcomes in India: the role of Caste and Religion. In: Thorat S, Newman K, editors. Blocked by Caste: economic discrimination in modern India. Oxford University Press; 2010. pp. 179–207.

  66. Hatzenbuehler ML, Phelan JC, Link BG. Stigma as a Fundamental cause of Population Health inequalities. Am J Public Health. 2013;103:813–21.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Jayachandran S. The roots of gender inequality in developing countries. Annu Rev Econ. 2015;7:63–88.

    Article  Google Scholar 

  68. Mitchell T. 4. Attitudes about caste. Pew Research Center’s Religion & Public Life Project. 2021. https://www.pewresearch.org/religion/2021/06/29/attitudes-about-caste/. Accessed 3 Jun 2023.

  69. Basu I. Elite discourse coalitions and the governance of ‘smart spaces’: politics, power and privilege in India’s Smart cities Mission. Polit Geogr. 2019;68:77–85.

    Article  Google Scholar 

  70. Jodhka S. Caste in contemporary India. Routledge; 2017.

  71. Jha R. Can urbanisation be the panacea for India’s caste issues? orfonline.org. 2019. https://www.orfonline.org/expert-speak/can-urbanisation-the-panacea-for-indias-caste-issues-49835. Accessed 14 May 2024.

  72. Ho CS, Wong SY, Chiu MM, Ho RC. Global prevalence of elder abuse: a Meta-analysis and Meta-regression. East Asian Arch Psychiatry off J Hong Kong Coll Psychiatr Dong Ya Jing Shen Ke Xue Zhi Xianggang Jing Shen Ke Yi Xue Yuan Qi Kan. 2017;27:43–55.

  73. Nair S, Sawant N, Thippeswamy H, Desai G. Gender issues in the care of Elderly: a narrative review. Indian J Psychol Med. 2021;43(5 Suppl):S48–52.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Yon Y, Mikton CR, Gassoumis ZD, Wilber KH. Elder abuse prevalence in community settings: a systematic review and meta-analysis. Lancet Glob Health. 2017;5:e147–56.

    Article  PubMed  Google Scholar 

  75. Dhak B. Gender difference in health and its determinants in the old-aged population in India. J Biosoc Sci. 2009;41:625–43.

    Article  PubMed  Google Scholar 

  76. Khera P. Macroeconomic impacts of gender inequality and informality in India. IMF Work Pap; 2016.

  77. Patel V, Kirkwood BR, Pednekar S, Pereira B, Barros P, Fernandes J, et al. Gender Disadvantage and Reproductive Health Risk Factors for Common Mental Disorders in Women: A Community Survey in India. Arch Gen Psychiatry. 2006;63:404–13.

    Article  PubMed  Google Scholar 

  78. Sekher TV, Hatti N. Disappearing daughters and intensification of gender bias: evidence from two village studies in South India. Sociol Bull. 2010;59:111–33.

    Article  Google Scholar 

  79. Agewell Foundation. Gender discrimination among older women in india, Agewell study 2015. 2015.

  80. Kumar N, Rani R. Regional disparities in Social Development: evidence from States and Union territories of India. South Asian Surv. 2019;26:1–27.

    Article  Google Scholar 

  81. Sebastian D, Sekher TV. Abuse and neglect of elderly in Indian families: findings of elder abuse screening test in Kerala. J Indian Acad Geriatr. 2010;6:57–9.

    Google Scholar 

  82. Richards L, Maharani A, Präg P. Subjective social status and allostatic load among older people in England: a longitudinal analysis. Soc Sci Med. 2023;320:115749.

    Article  PubMed  Google Scholar 

  83. Williams DR, Yan Yu null, Jackson JS, Anderson NB. Racial Differences in Physical and Mental Health: Socio-economic Status, Stress and Discrimination. J Health Psychol. 1997;2:335–51.

  84. Lewis TT, Yang FM, Jacobs EA, Fitchett G. Racial/Ethnic differences in responses to the Everyday discrimination scale: a Differential Item Functioning Analysis. Am J Epidemiol. 2012;175:391–401.

    Article  PubMed  PubMed Central  Google Scholar 

  85. McConnell EA, Janulis P, Phillips G, Truong R, Birkett M. Multiple minority stress and LGBT Community Resilience among sexual minority men. Psychol Sex Orientat Gend Divers. 2018;5:1–12.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Bowleg L. The Problem with the phrase women and minorities: Intersectionality—an important theoretical Framework for Public Health. Am J Public Health. 2012;102:1267–73.

    Article  PubMed  PubMed Central  Google Scholar 

  87. Denise EJ. Multiple disadvantaged statuses and Health: the role of multiple forms of discrimination. J Health Soc Behav. 2014;55:3–19.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The current study did not receive any funding as is based on a secondary data from the Longitudinal Aging Study in India. The LASI Project was funded by the Ministry of Health and Family Welfare, Government of India, the National Institute on Aging (R01 AG042778, R01 AG030153), and United Nations Population Fund, India.

Funding

The analysis received no funding.

Author information

Authors and Affiliations

  1. Department of Family and Generations, International Institute for Population Sciences, Mumbai, Maharashtra, 400088, India

    T. V Sekher

  2. Department of Sociology and Criminology, Kent State University, Kent, OH, 44242, USA

    Manacy Pai

  3. Center for Healthy Aging, The Pennsylvania State University, University Park, PA, 16802, USA

    T. Muhammad

Authors
  1. T. V Sekher
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Manacy Pai
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. T. Muhammad
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

TVS and TM conceived and designed the research paper and analyzed the data; MP, TM, and TVS wrote the manuscript; All authors made critical revisions of the manuscript for key intellectual content. All authors read and approved the final version of the manuscript and have agreed to the authorship and order of authorship for this manuscript.

Corresponding author

Correspondence to T. Muhammad.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the Indian Council of Medical Research (ICMR) Ethics Committee in January 2017 and written or oral informed consent was obtained from the participants. All methods were carried out in accordance with relevant guidelines and regulations and in accordance with the World Medical Association Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sekher, T.V., Pai, M. & Muhammad, T. Subjective social status and socio-demographic correlates of perceived discrimination among older adults in India. BMC Geriatr 24, 617 (2024). https://doi.org/10.1186/s12877-024-05114-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12877-024-05114-x

Keywords

BMC Geriatrics

ISSN: 1471-2318

Contact us