Determinants of Multimorbidity among The Elderly Population in Indonesia

Abstract

Multimorbidity is the presence of two or more chronic diseases in one person. Multimorbidity prevalence increases with age, especially in the elderly. This study aimed to determine the prevalence of multimorbidity in elderly population in Indonesia and its determinant. Data were taken from the fourth survey of the Indonesian Family Life Survey (IFLS) which held in 2007. IFLS is a continuing longitudinal socio-economic and health survey. The sample used in the analysis were 2,960 elderly (≥ 60 years). Logistic regression was performed to determine the prevalence and determinants of multimorbidity in the elderly. The prevalence of multimorbidity were 15.8 % and was higher among low educational level, unemployed, current smokers, mild physical activity, overweight/obese and lower consumption of vegetables and fruit. Multivariate analysis showed that low educational level, unemployed, current smoker and ex smoker, overweight/obese, mild physical activity and lower consumption of vegetables and fruit were associated with multimorbidity. The results showed that the prevalence of multimorbidity in Indonesian elderly is quite high especially those with poor health behaviors and low socioeconomic conditions. Strategies to increase healthy behaviors and improve socio-economic conditions may decrease the prevalence of multimorbidity. Keywords: Determinant, elderly, multimorbidity AbstrakMultimorbiditas adalah kehadiran dua atau lebih penyakit kronis pada satu orang. Prevalensi multimorbiditas meningkat dengan usia, terutama pada lanjut usia (lansia). Penelitian ini bertujuan untuk mengetahui prevalensi dan determinan multimorbiditas pada lansia di Indonesia. Data diambil dari survei keempat Indonesian Family Life Survey (IFLS) yang diadakan pada tahun 2007. IFLS adalah survei sosial ekonomi dan kesehatan longitudinal di Indonesia. Sampel yang digunakan dalam analisis adalah 2.960 lansia (≥ 60 tahun). Regresi logistik dilakukan untuk menentukan prevalensi dan determinan multimorbiditas pada lansia. Hasil penelitian menunjukkan prevalensi multimorbiditas sebesar 15,8%, dengan prevalensi lebih tinggi pada lansia yang overweight/obesitas, tingkat pendidikan rendah, tidak bekerja, perokok saat ini, aktivitas fisik ringan, overweight/obesitas, dan kurangnya konsumsi sayur dan buah. Analisis multivariat menunjukkan bahwa tingkat pendidikan yang rendah, tidak bekerja, perokok saat ini dan pernah merokok, overweight/obesitas, aktivitas fisik ringan, serta kurangnya konsumsi sayuran dan buah berhubungan dengan multimorbiditas. Hasil penelitian menunjukkan bahwa prevalensi multimorbiditas pada lansia Indonesia cukup tinggi terutama mereka dengan perilaku kesehatan yang buruk dan kondisi sosial ekonomi yang rendah. Strategi untuk meningkatkan perilaku sehat dan meningkatkan kondisi sosial-ekonomi dapat menurunkan prevalensi multimorbiditas pada lansia.

Prevalence and factors associated with multimorbidity among older adults in Malaysia: a population-based cross-sectional study

“…In our study, multimorbidity was associated with advanced aged and being unemployed which was similar to the findings in another study. 10 It has been suggested that oldest old were more likely to have multimorbidity than younger older adults because of the physiological changes that occur with advancing age. 7 40 As for being unemployed, a study in Korea showed the proportion of unemployed older adults were higher among those with obesity and physical inactivity.…”

“… 41 Additionally, obesity and physical inactivity have been shown to be associated with increased risk for multimorbidity in older adults. 10 …”

Effect of multimorbidity on utilisation and out-of-pocket expenditure in Indonesia: quantile regression analysis

“…Evidence from high-income countries (HICs) suggest that multimorbidity imposes a substantial economic burden, however, evidence in LMICs and in particular Indonesia is sparse [ 14 – 16 ]. Moreover, previous studies in LMICs utilised regression models, such as ordinary least squares (OLS), generalized linear model (GLM), or logistic models, that estimate the impact of multimorbidity on outcomes at the mean or population average [ 3 , 17 – 19 ]. These regression methods often assume that regression coefficients are constant across the population, ignoring the fact that the effect of multimorbidity may vary in those with higher utilisation than those with lower utilisation.…”

Obesity Indicators and C-Reactive Protein in Indonesian Adults (More than Equal to 40 Years Old): The Indonesian Family Life Survey 5

“…Multimorbidity was defined as two or more chronic NCDs. 24 Simple logistic regression was used to compare categorical variables. Those found significant in the bivariate analysis at the p-value < 0.25 level were entered into multivariate analysis.…”