Factors Associated with Poor Socioeconomic Status Among Malaysian Older Adults: an Analysis According to Urban and Rural Settings

Overview

Journal BMC Public Health

Publisher Biomed Central

Specialty Public Health

Date 2019 Jun 15

PMID 31196023

Citations 33

Authors

Suzana Shahar

Divya Vanoh

Arimi Fitri Mat Ludin

Devinder Kaur Ajit Singh

Tengku Aizan Hamid

Affiliations

Soon will be listed here.

Abstract

Background: Poverty at old age is associated with poor dietary habit, nutritional status and higher rates of chronic diseases and psychosocial problems. However, there is limited information about this matter according to urban and rural settings. The aim of this study was to identify dietary, nutritional, physical and cognitive factors associated with poor socioeconomic status (SES) among older adults according to urban and rural settings in Malaysia.

Methods: An analysis was conducted among 2237 older adults who participated in a longitudinal study on aging (LRGS TUA). This study involved four states in Malaysia, with 49.4% from urban areas. Respondents were divided into three categories of SES based on percentile, stratified according to urban and rural settings. SES was measured using household income.

Results: The prevalence of low SES was higher among older adults in the rural area (50.6%) as compared to the urban area (49.4%). Factors associated with low SES among older adults in an urban setting were low dietary fibre intake (Adj OR:0.91),longer time for the Timed up and Go Test (Adj OR:1.09), greater disability (Adj OR:1.02), less frequent practice of caloric restriction (Adj OR:1.65), lower cognitive processing speed score (Adj OR:0.94) and lower protein intake (Adj OR:0.94). Whilst, among respondents from rural area, the factors associated with low SES were lack of dietary fibre intake (Adj OR:0.79), lower calf circumference (Adj OR: 0.91), lesser fresh fruits intake (Adj OR:0.91), greater disability (Adj OR:1.02) and having lower score in instrumental activities of daily living (Adj OR: 0.92).

Conclusion: Lower SES ismore prevalent in rural areas. Poor dietary intake, lower fitness and disability were common factors associated with low in SES, regardless of settings. Factors associated with low SES identifiedin both the urban and rural areas in our study may be useful inplanning strategies to combat low SES and its related problems among older adults.

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References

Bassuk S, Berkman L, Amick 3rd B . Socioeconomic status and mortality among the elderly: findings from four US communities. Am J Epidemiol. 2002; 155(6):520-33. DOI: 10.1093/aje/155.6.520. View

Folstein M, Folstein S, McHugh P . "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975; 12(3):189-98. DOI: 10.1016/0022-3956(75)90026-6. View

Katz S, Ford A, Moskowitz R, Jackson B, JAFFE M . STUDIES OF ILLNESS IN THE AGED. THE INDEX OF ADL: A STANDARDIZED MEASURE OF BIOLOGICAL AND PSYCHOSOCIAL FUNCTION. JAMA. 1963; 185:914-9. DOI: 10.1001/jama.1963.03060120024016. View

Graf C . The Lawton instrumental activities of daily living scale. Am J Nurs. 2008; 108(4):52-62. DOI: 10.1097/01.NAJ.0000314810.46029.74. View

Hughes M, Waite L, Hawkley L, Cacioppo J . A Short Scale for Measuring Loneliness in Large Surveys: Results From Two Population-Based Studies. Res Aging. 2008; 26(6):655-672. PMC: 2394670. DOI: 10.1177/0164027504268574. View

Donini L, Savina C, Piredda M, Cucinotta D, Fiorito A, Inelmen E . Senile anorexia in acute-ward and rehabilitations settings. J Nutr Health Aging. 2008; 12(8):511-7. DOI: 10.1007/BF02983203. View

Liu J, Chi I, Chen G, Song X, Zheng X . Prevalence and correlates of functional disability in Chinese older adults. Geriatr Gerontol Int. 2009; 9(3):253-61. DOI: 10.1111/j.1447-0594.2009.00529.x. View

Andrews G, Kemp A, Sunderland M, Von Korff M, Ustun T . Normative data for the 12 item WHO Disability Assessment Schedule 2.0. PLoS One. 2009; 4(12):e8343. PMC: 2791224. DOI: 10.1371/journal.pone.0008343. View

Norimah Jr A, Safiah M, Jamal K, Haslinda S, Zuhaida H, Rohida S . Food Consumption Patterns: Findings from the Malaysian Adult Nutrition Survey (MANS). Malays J Nutr. 2012; 14(1):25-39. View

10.

Shahar S, Earland J, Abdulrahman S . Validation of a Dietary History Questionnaire against a 7-D Weighed Record for Estimating Nutrient Intake among Rural Elderly Malays. Malays J Nutr. 2012; 6(1):33-44. View

11.

Wunderlich S, Brusca J, Johnson-Austin M, Bai Y, O Malley M . Eating behaviors of older adults participating in government-sponsored programs with different demographic backgrounds. Glob J Health Sci. 2012; 4(6):204-15. PMC: 4776999. DOI: 10.5539/gjhs.v4n6p204. View

12.

Robertson T, Batty G, Der G, Fenton C, Shiels P, Benzeval M . Is socioeconomic status associated with biological aging as measured by telomere length?. Epidemiol Rev. 2012; 35:98-111. PMC: 3578449. DOI: 10.1093/epirev/mxs001. View

13.

Donini L, Poggiogalle E, Piredda M, Pinto A, Barbagallo M, Cucinotta D . Anorexia and eating patterns in the elderly. PLoS One. 2013; 8(5):e63539. PMC: 3642105. DOI: 10.1371/journal.pone.0063539. View

14.

Conklin A, Maguire E, Monsivais P . Economic determinants of diet in older adults: systematic review. J Epidemiol Community Health. 2013; 67(9):721-7. PMC: 3756433. DOI: 10.1136/jech-2013-202513. View

15.

Nicklett E, Kadell A . Fruit and vegetable intake among older adults: a scoping review. Maturitas. 2013; 75(4):305-12. PMC: 3713183. DOI: 10.1016/j.maturitas.2013.05.005. View

16.

Hurst L, Stafford M, Cooper R, Hardy R, Richards M, Kuh D . Lifetime socioeconomic inequalities in physical and cognitive aging. Am J Public Health. 2013; 103(9):1641-8. PMC: 3780680. DOI: 10.2105/AJPH.2013.301240. View

17.

Mohd Fahmi Teng N, Shahar S, Rajab N, Manaf Z, Johari M, Wan Ngah W . Improvement of metabolic parameters in healthy older adult men following a fasting calorie restriction intervention. Aging Male. 2013; 16(4):177-83. DOI: 10.3109/13685538.2013.832191. View

18.

Shahar S, Earland J, Rahman S . Food intakes and habits of rural elderly Malays. Asia Pac J Clin Nutr. 2014; 9(2):122-9. DOI: 10.1046/j.1440-6047.2000.00147.x. View

19.

da Silva Alexandre T, de Oliveira Duarte Y, Ferreira Santos J, Wong R, Lebrao M . Prevalence and associated factors of sarcopenia among elderly in Brazil: findings from the SABE study. J Nutr Health Aging. 2014; 18(3):284-90. DOI: 10.1007/s12603-013-0413-0. View

20.

Barrera G, Cases T, Bunout D, de la Maza M, Leiva L, Rodriguez J . Associations between socioeconomic status, aging and functionality among older women. Geriatr Nurs. 2014; 38(4):347-351. DOI: 10.1016/j.gerinurse.2014.08.012. View