Profile of Food and Nutrient Intake Among Indonesian Elderly … · 2014. 2. 1. · 265 ORIGINAL ARTICLE Acta Medica Indonesiana - The Indonesian Journal of Internal Medicine Profile

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ORIGINAL ARTICLE

Acta Medica Indonesiana - The Indonesian Journal of Internal Medicine

Profile of Food and Nutrient Intake Among Indonesian Elderly Population and Factors Associated with Energy Intake: a Multi-centre Study

Siti Setiati1, Kuntjoro Harimurti1, Esthika Dewiasty1, Rahmi Istanti1, Yudho M. Mupangati2, Dwi Ngestiningsih2, Yosef Purwoko2, IGP. Suka Aryana3, R.A. Tuty Kuswardhani3, I Dewa Putu Pramantara4, Muhamad Apandi5, Lazuardhi Dwipa5, Fatichati Budiningsih6, Rose Dinda7, Novira Widajanti8, Pirma Siburian9, Sri Sunarti10, Syamsu Umar11, Edward Jim12, Junaidi-AR13

1 Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia. 2 Faculty of Medicine, University of Diponegoro, Semarang, Indonesia. 3 Faculty of Medicine, University of Udayana, Denpasar, Bali, Indonesia. 4 Faculty of Medicine, University of Gajah Mada, Yogyakarta, Indonesia. 5 Faculty of Medicine, University of Padjajaran, Bandung, Indonesia. 6 Faculty of Medicine, University of Sebelas Maret, Surakarta, Indonesia. 7 Faculty of Medicine, University of Andalas, Padang, Indonesia. 8 Faculty of Medicine, University of Airlangga, Surabaya, Indonesia. 9 Faculty of Medicine, University of Sumatera Utara, Indonesia. 10 Faculty of Medicine, University of Brawijaya, Malang, Indonesia. 11 Faculty of Medicine, University of Syiah Kuala, Aceh, Indonesia. 12 Faculty of Medicine, University of Sam Ratulangi, Manado, Indonesia. 13 Faculty of Medicine, University of Sriwijaya, Palembang, Indonesia.

Correspondence mail:Prof. Siti Setiati, M.D., PhD., Division of Geriatric, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia. Jl. Salemba 6, Jakarta 10430, Indonesia. email: [email protected].

AbStrAkTujuan: untuk mendapatkan profil asupan makanan dan zat gizi usia lanjut Indonesia dan faktor-faktor yang

memengaruhi asupan energi. Metode: penelitian dengan desain cross sectional dilakukan secara multi-centre di 13 rumah sakit di Indonesia terhadap 387 usia lanjut. Data yang dikumpulkan meliputi karakteristik demografi, status fungsional, status kognitif, status mental, status gizi, asupan makanan, aktivitas, dan penyakit kronik yang diderita. Analisis data dilakukan dengan uji statistic Chi-square dan regresi logistik. Hasil: sebagian besar subjek (58.4%) adalah wanita dan memiliki tingkat pendidikan SMA atau lebih. Rerata asupan energi adalah 1266.74 (336.51) kilocalories. Asupan kalsium dan protein subjek kurang dari angka kecukupan gizi yang dianjurkan (AKG). Wanita (OR 0.23; 95% CI 0.139–0.390) dan subjek yang menderita osteoporosis OR 0.48; 95% CI 0.25–0.93) memiliki risiko yang lebih rendah untuk memiliki asupan energi kurang dari 80% AKG, sedangkan subjek dengan tingkat pendidikan kurang atau sama dengan SMP (OR 1.96; 95% CI 1.21–3.18) memiliki risiko yang lebih tinggi untuk memiliki asupan energi <80% AKG. Kesimpulan: asupan energi pada usia lanjut di Indonesia didapatkan tidak adekuat. Wanita dan subjek yang menderita osteoporosis memiliki risiko yang lebih rendah untuk memiliki asupan energi kurang dari 80% AKG, sedangkan subjek dengan tingkat pendidikan kurang atau sama dengan SMP memiliki risiko yang lebih tinggi untuk memiliki asupan energi <80% AKG.

Kata kunci: usia lanjut, asupan zat gizi, asupan makanan, zat gizi makro, zat gizi mikro.

AbStrActAim: to obtain profile of food and nutrient intake in Indonesian elderly population and factors associated

with energy intake. Methods: multi-center cross sectional study in 13 hospitals across Indonesia was conducted

Siti Setiati Acta Med Indones-Indones J Intern Med

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INtroductIoNElderly populations are increasing in

both developed and developing countries. In developing countries, the increase of elderly population is faster than the general population as a whole. Furthermore, the elderly population is itself getting older.1 The elderly population in Indonesia is also estimated to be increasing, by the year 2020 it will reach 29 million (11.2% of the total population in Indonesia). As the elderly population increases, health-related problems will also increase in this population. Nutrition is an important issue which can have a pronounced effect in the elderly.2

The elderly population have physical and economic problems that can limit food intake, such as decline in sense of smell and taste, problems with chewing and swallowing, living alone, and limited financial resources.3 Health status of the elderly may be strongly influenced by inadequate nutrition.4 Inadequate dietary intake and low body mass are associated with function decline and failure to thrive in elderly. Thus, poor dietary habits and inadequate nutrient intake are of concern in the elderly. One study shows that 80% of elderly subjects report inadequate intake of four or more nutrients.2

Information on the quantity and composition of dietary intake in Indonesian elderly population is limited and even less is known about factors associated with energy intake of the elderly. Specific characteristics of Indonesian geriatric outpatients such as high prevalence of illness, low income, low level of education, social isolation, and limited access to health services,

contribute to physical limitations, causing this population to have inadequate intake. Information about food and nutrient intake and factors associated with energy intake is important for health professionals and policy makers in order to improve well-being and prevent diseases in this population. The aim of this study were to obtain profile of food and nutrient intake and factors associated with energy intake of the elderly population.

MEthodS

This multi-center cross-sectional study was conducted among 387 elderly outpatients (aged 60 years and older) in 15 cities in Indonesia between January-April 2011, who had visited the geriatric clinic of government hospitals in these cities. The elderly visited the clinic for having medication of their illness and most of them had more than three chronic diseases. The exclusion criteria were those who have inability to answer the assessment questionnaire due to serious hearing problems or severe communication disorders, and refused to participate in the study. All subjects were informed about the objectives and contents of the study. Verbal informed consents were obtained from all participants.

data collectionAll subjects were evaluated through face-to-

face interview technique conducted by trained staffs. A structured questionnaire was applied to collect demographic data such as age, sex, educational status, present activities using questions such as “do you still actively do things

among 387 elderly who had attended geriatric clinics. Data collected including demographic characteristics, functional status, cognitive status, mental status, nutritional status, food intake, present activities, and data on chronic diseases. Chi square and logistic regression tests were performed to analyze the data. Results: most of subjects (58.4%) were women and had educational background senior high school or higher degree (61.1%). The average of energy intake was 1266.74 (336.51) kilocalories. Calcium and protein intake were below the recommended of dietary allowance. female sex (OR 0.23; 95% CI 0.139–0.390) and osteoporotic subjects (OR 0.48; 95% CI 0.25–0.93) have lower risk for having <80% RDA daily energy intake, while lower educational level (OR 1.96; 95% CI 1.21–3.18) has higher risk for having <80% RDA daily energy intake. Conclusion: total energy intake were inadequate in the elderly. Female sex and osteoporotic subjects have lower risk for having <80% RDA daily energy intake, while lower educational level has higher risk for having <80% RDA daily energy intake.

Key words: elderly, nutrient intake, food intake, micro nutrient, macro nutrient.

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every day?”, co-morbidities, functional status, cognitive status, nutritional status, mental status, and food and nutrient intake.

Data on co-morbidities was based on self-reported information. Functional status was measured by Barthel’s Activity of Daily Living (ADL) Index questionnaire. We defined independent functional status as having an ADL score equal to 20, and dependent functional status as having an ADL score of less than 20. Cognitive and mental status were measured using the Mini Mental State Examination (MMSE) questionnaire and Geriatric Depression Scale (GDS) questionnaire respectively. We defined depression or susceptible to depression if the GDS score was >5 and normal if the GDS score was <5. Normal cognitive status was defined as having a MMSE score of 23-30, and cognitive dysfunction was defined as having a MMSE score of less than 23. Nutritional status was assessed using the Mini Nutritional Assessment (MNA) questionnaire. We defined normal nutritional status as having a MNA score >23.5 and malnutrition as having a MNA score of <23.5. Data on food and nutrient intake was obtained using a 24-hour food recall method by trained interviewers. We divided energy intake as >80% Recommended Dietary Allowance (RDA) for Indonesian elderly and <80% RDA for Indonesian elderly. Food intake was divided into the following groups: rice and noodles, meat, eggs, fish, coconut milk, dairy products, legumes and nuts, tempeh and tofu, vegetables, fruits, sugar products, oil/fat, and non alcoholic beverages.

data Analyses

Characteristics of subjects presented in number and percentages including age, sex, education, and chronic diseases. Bivariate analysis using Chi square test were done between each independent variables and energy intake. Then a multivariate analysis using logistic regression were performed. A 2-sided p-value less than 0.05 was considered to indicate statistical significance. Data were analyzed using SPSS statistical package software.

rESultS Most subjects in this study were women

(58.4%), ages 60-69 years (52.5%) and had an educational background of senior high school or higher (60.99%). More than half of the subjects were not active on a daily basis (87.82%) and had three or more chronic diseases (56.8%). The most common disease found in subjects was hypertension (74.2%). We found 62.36% of subjects to be independent, 87.3% had normal mental status, and 90.4% had normal cognitive function. Based on MNA Scores, only 17.6% of subjects had risk of malnutrition. Table 1 describes the characteristics of subjects.

Nutrient intake analysis results of 387 subjects show that the mean energy intake was 1266.74 (336.51) kcalories, protein intake was 44.74 (15.47) gr, fat intake was 41.23 (17.89) gr, and carbohydrate intake was 172.02 (57.87) gr. Table 2 shows mean of nutrient intake. The nutrient intake of energy and carbohydrate were significantly different in both sex (p<0.05).

Figure 1 shows the subjects’ proportion of macro and micro nutrient intake based on percent RDA. More than 50% of subjects had macro and micronutrient intake less than 80% RDA, except for protein, fat, and vitamin A intake.

Average daily food intake is presented in grams per day for the total amount of foods consumed, and by each major food group. All food items reported for intake were converted into grams per day and then grouped. Table 3 shows average food intake of elderly men and women. Number of total food intake and rice and noodles were higher significantly among elderly men.

Table 4 shows the results of bivariate analyses between associated factors and energy intake. Using criteria of p-value <0.25, candidate variables for multivatiate analysis were age, sex, education level, hypertension, osteoporosis, osteoarthritis, hyperuricemia, vision impairment, and functional status.

Table 5 shows the results of multiple logistic regression analysis, which shows that female sex (OR 0.23; 95% CI 0.139–0.390) and osteoporotic subjects (OR 0.48; 95% CI 0.25–0.93) have


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table 1. Subject characteristics

characteristics N (%)

Sex

- Men 161 (41.6)

- Women 226 (58.4)

Age

- 60-69 203 (52.5)

- 70-79 151 (39.0)

- ≥80 33 (8.5)

Formal education

- None 12 (3.1)

- Elementary school 71 (18.3)

- Middle school 68 (17.6)

- High school 131 (33.9)

- University 105 (27.2)

Activity

- Active 47 (12.1)

- Not active 339 (87.6)

Energi Intake

- <80% RDA 264 (68.2)

- ≥80% RDA 123 (31.8)

Number of chronic disease

- <3 167 (43.2)

- ≥3 220 (56.8)

Commorbidities

- Hypertension 287 (74.2)

- Diabetes mellitus 150 (38.8)

- Vision impairment 135 (34.9)

- Osteoarthritis 105 (27.1)

- Osteoporosis 45 (11.6)

- Hearing impairment 89 (23.0)

- Coronary heart disease 46 (11.9)

- Chronic kidney disease 27 (7.0)

- Hypercholesterolemia 81 (20.9)

- Hyperurisemia 38 (9.8)

- Urinary incontinence 16 (4.1)

- Insomnia 35 (9.0)

- Chronic heart disease 9 (2.3)

Functional status

- Independent 246 (63.6)

- Mild dependence 135 (34.9)

- Moderate dependence 2 (0.5)

- Severe dependence 1 (0.3)

- Totally dependence 3 (0.8)

Mental status

- Normal 338 (87.3)

- Susceptible to depression 43 (11.1)

- Depression 6 (1.6)

table 1. Subject characteristics

characteristics N (%)

Cognitive status

- Normal 350 (90.4)

- Mild cognitive dysfunction 23 (5.9)

- Severe cognitive dysfunction 14 (3.6)

Nutritional status

- Normal 268 (69.3)

- Risk of malnutrition 68 (17.6)

- Malnutrition 20 (5.2)

Anthropometric measurements

- Height (cm) 156.1 (8.6)

- Weight (kg 58.6 (10.4)

- Body mass index (kg/m2) 24.1 (4.0)

- Upper arm circumference (cm) 27.3 (4.3)

- Calf circumference (cm) 35.9 (23.9)

table 2. Mean of nutrient intake

Nutrient Men (n=161) Women (n=226)

Energi (Kcal) 1313 + 341 1234 + 330*

% RDA 64.04 77.12*

Protein (g/d) 45.3 + 1.1 44.3 + 1.5

% RDA 77.42 91.53*

Carbohydrates (g/d) 184 + 4.7 164 + 4.8*

% RDA 58.40 66.93*

Fat (g/d) 41 + 2 42 + 1.7

% RDA 75.28 97.34*

Fibers (g/d) 9.4 + 5 9.3 + 5.3

% RDA 37.67 37.33

Calcium (mg/d) 257 + 2.2 267 + 2.2

% RDA 43.65 46.63

Iron (mg/d) 8.0 + 4.6 9.3 + 13.2

% RDA 61.89 77.31

Zinc (mg/d) 5.2 + 1.9 5.3 + 2.5

% RDA 38.72 54.25*

Folate (mg/d) 3.1 + 10.5 4.5 + 14.1

% RDA 0.76 1.14

Vitamin A (mg RE/d) 979 + 1156 958 + 1073

% RDA 163.15 191.69

Vitamin E (mg/d) 0.32 + 1.38 0.37 + 1.21

% RDA 2.11 2.45

Vitamin C (mg/d) 54 + 57 64 + 78

% RDA 59.79 85.82*

*Significantly different from men, p<0.05


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table 3. Mean of food intake

Food groupMen Women

Mean (sd)g/day

Mediang/day

range (25th-75th percentile)

Mean (sd)g/day

Mediang/day

range (25th-75th percentile)

Total food* 933.1 (260.9) 915 750.0 – 1101.1 848.9 (248.7) 951.0 759.0 – 1135.0

Animal proteins 117.1 (80.6) 115.0 70.0- 150.0 119.3 (71.4) 115 70 – 150

Meat 20.8 (35.2) 0.0 0.0 – 40.0 28.0 (43.8) 0.0 0.0 – 40.0

Eggs 14.6 (28.4) 0.0 0.0 – 25.0 17.3 (28.9) 0.0 0.0 -25.0

Fish 58.3 (57.1) 50.0 0.0 – 100.0 50.5 (52.4) 50.0 0.0 – 100.0

Dairy products 23.3 (65.2) 0.0 0.0 – 20.0 23.5 (54.2) 0.0 0.0 – 20.0

Plant proteins* 791.5 (256.7) 660.0 516.3 – 820.0 688.6 (234.7) 660.0 516.3 – 820.0

Legumes and nuts 31.1 (58.3) 0.0 0.0 – 15.0 18.1 (46.1) 0.0 0.0 – 15.0

Tempeh and tofu 67.0 (102.5) 40.0 0.0 – 100.0 58.9 (68.6) 40.0 0.0 – 100.0

Vegetables 162.2 (118.4) 140.0 63.8 – 228.8 158.9 (119.3) 140.0 63.8 – 228.8

Fruits 107.4 (127.9) 80.0 0.0 – 162.5 102.8 (107.1) 80.0 0.0 – 162.5

Rice and noodles* 417.6 (161.9) 315.0 250.0 – 425.0 342.5 (138.9) 315.0 250.0 – 425.0

Coconut milk 6.1 (22.5) 0.00 0.0 – 0.0 9.9 (30.2) 0.0 0.0-0.0

Plant: animal ratio* 8.2 (6.0) 6.4 4.6-9.1 7.5 (6.5) 5.5 3.9-8.4

Others 61.4 (67.6) 41.0 14.0-80.0 61.7 (65.4) 35.0 15.0-98.0

Sugar products 40.1 (57.3) 20 0-50.5 43.9 (60.1) 20.0 0-63.5

Oil/ fat 18.7 (32.1) 10.0 0-2.0 15.9 (24.8) 10.0 0-15.8

Non alcoholic beverages 2.6 (7.3) 0 0.0-5.0 1.8 (6.1) 0 0.0-0.0

*Significant difference between sex P<0.01 (Kolmogrov-Smirnov test)

Figure 1. Subject proportion of Macro and Micro nutrient intake based on percent RDA

lower risk for having <80% RDA daily energy intake, while lower educational level (OR 1.96; 95% CI 1.21 – 3.18) has higher risk for having <80% RDA daily energy intake.

Based on the multivariate analysis results, we conducted further descriptive analyses of food intake. that subjects with lower educational

backgrounds consumed less amount of eggs We found, fats/oil, fruits and juice, legumes, and snacks. It was also found that osteoporotic subjects consumed eggs, fruits and juice, seafood, milk, and other non-alcoholic beverages more than non-osteoporotic subjects did (data no shown).


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table 4. Bivariate analysis on factors associated with energy intake

risk FactorsEnergy intake

or (95% cI) P value<80% rdA N(%)

>80% rdA N(%)

Age>70 years 116 (63.0) 68 (37.0) 0.63 (0.41 – 0.98) *0.037

60-69 years 148 (72.9) 55 (27.1)

SexFemale 129 (57.1) 97 (42.9) 0.26 (0.16 – 0.42) *0.001

Male 135 (83.9) 26 (16.1)

EducationJunior high school and lower 110 (72.8) 41 (27.2) 1.43 (0.91 – 2.24) 0.118

Senior high school and Higher 154 (65.3) 82 (34.7)

ActivityNon active 22 (16.7) 110 (83.3) 0.78 (0.41– 1.57) 0.509

Active 34 (72.3) 13 (27.7)

hypertensionYes 189 (65.9) 98 (34.1) 0.64 (0.38 – 1.08) 0.091

No 75 (75.0) 25 (25.0)

diabetes mellitusYes 104 (69.3) 46 (30.7) 1.09 (0.70 – 1.69) 0.708

No 160 (67.5) 77 (32.5)

osteoporosisYes 23 (51.1) 22 (48.9) 0.44 (0.23 – 0.82) *0.009

No 241 (70.5) 101 (29.5)

chronic kidney diseaseYes 20 (74.1) 7 (25.9) 1.34 (0.56 – 3.30) 0.498

No 244 (67.8) 116 (32.2)

coronary heart diseaseYes 20 (74.1) 7 (25.9) 0.96 (0.49 – 1.85) 0.898

No 244 (67.8) 116 (32.2)

osteoarthritisYes 64 (60.9) 41 (39.0) 0.64 (0.40- 1.02) 0.061

No 200 (70.9) 82 (29.1)

hypercholesterolemiaYes 59 (72.8) 22 (27.2) 1.32 (0.77 – 2.28) 0.315

No 205 (66.9) 101 (33.0)

hyperuricemiaYes 30 (11.4) 8 (6.5) 1.84 (0.82 – 4.15) 0.135

No 234 (88.6) 115 (93.5)

urinary incontinenceYes 13 (81.3) 3 (18.7) 2.07 (0.58 – 7.41) 0.253

No 251 (67.7) 120 (32.3)

InsomniaYes 26 (74.3) 9 (25.7) 1.38 (0.63 – 3.05) 0.419

No 238 (67.6) 114 (32.4)

hearing impairmentYes 63 (70.8) 26 (29.2) 1.17 (0.69 – 1.96) 0.553

No 201 (67.4) 97 (32.6)


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table 4. Bivariate analysis on factors associated with energy intake

risk FactorsEnergy intake

or (95% cI) P value<80% rdA N(%)

>80% rdA N(%)

chronic liver diseaseYes 8 (88.9) 1 (11.1) 3.81 (0.47 – 30.82) 0.282

No 256 (67.7) 122 (32.3)

Vision impairmentYes 100 (74.1) 35 (25.9) 1.53 (0.96 – 2.44) 0.07

No 164 (65.1) 88 (34.9)

Functional status

Dependent 86 (60.9) 55 (39.1) 0.597 (0.36 – 0.93) *0.021

Normal 178 (72.4) 68 (27.6)

Mental statusSucceptible to depression 34 (69.4) 15 (30.6) 1.06 (0.56 – 2.31) 0.851

Normal 230 (68.0) 108 (31.9)

cognitive statusCognitive dysfunction 26 (70.2) 11 (29.8) 1.11 (0.53-2.33) 0.778

Normal 238 (68.0) 112 (32.0)

Nutritional status

Malnutrition 62 (70.5) 26 (29.5) 1.19 (0.70 – 2.00) 0.524

Normal 179 (66.8) 89 (33.2)

table 5. Multivariate analysis on factors associated with energy intake

Variables coefficient or (95% cI) P-value

Sex (female) -1.457 0.23 (0.14 – 0.39) 0.001

Education (Junior high school and lower) 0.673 1.96 (1.21 – 3.18) 0.046

Osteoporosis -0.735 0.48 (0.25 – 0.93) 0.030

Constanta 1.549

dIScuSSIoN Sustaining good health in the elderly is

a major challenge to public health. Nutrition has an important role in protecting health and slowing disease progression.5 The most common diseases of the elderly are chronic diseases which are prolonged illnesses that are rarely cured completely, such as hypertension and diabetes mellitus. The prevalence of hypertension in this study was quite high (74.2%). This percentage was higher than those reported among the elderly population in Bahrain (15.4%).1 The prevalence of diabetes among Indonesian elderly was also higher than that of Bahrains for the same age group (38.8% and 12.9% respectively).1

This current study provides new data on nutrient and food intake of the elderly

population. Inadequate nutrition in elderly is often unrecognized but is a major problem that can affect nutritional status of this population. The reported prevalence of nutritional status in the elderly varied depending on the examined population and the diagnostic criteria used.6,7

Based on the Mini Nutritional Assessment scores, the prevalence of malnutrition in this study was quite small (5.2%) in general. This prevalence was lower compared to other studies in Asian countries (Japan and Iran) which found malnutrition rates of 19.9% and 12% respectively.8,9 Compared to other developing countries such as Uganda where the prevalence of undernourished elders was 33.3%, the prevalence of malnutrition among Indonesian elderly was lower.10 Despite the low prevalence


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of malnutrition in this study, it should be pointed out that the prevalence of malnutrition risk is quite large (17.6%). However, compared to previous studies where the the risk of malnutrition in elders was 56.7%, the prevalence found in this study was still lower.11 Nutrition intervention such as nutrition counseling that emphasizes balanced diet to ensure adequate intake are necessary to prevent this group from becoming malnourished.

In this study, we were able to describe nutrient and food intake of elderly outpatients. Our results suggest that elderly men have higher intake of energy, protein, carbohydrate, fibers, and vitamin A. This study found that both elderly men and women have energy intakes below the recommended guidelines of Indonesian aged 60 years and over (2050 kcal for men and 1600 kcal for women).12 Protein intake was also lower than the recommended value for both elderly men and women. The main source of protein consumed in this study was found to be that of plant proteins (grains). The second most common source of protein after is fish.

Fat intake was found to be higher in elderly women than the elderly men, and also lower than the recommended value. As similarly reported in the study conducted by Purba, the main source of fat in this study was also from oils.13 Oil was used to enhance flavor of foods such as vegetables, tempeh and tofu in traditional Indonesian cuisines mixed with herbs and spices.13

Calcium intake in this study was below the recommended dietary allowance (800 mg/day). This result was also lower in comparison to calcium intake of Australian elderly women (852 mg/day).14 Lower and inadequate micronutrient intake in elderly is common. Elders usually take multivitamin supplements in effort to compensate for inadequate miconutrient intake, however the benefits of this practice had not been examined yet.9

Food intake is different among countries, which may be based upon personal preferences, habit or tradition, social pressure, availability, convenience, economics and/or nutritional value. Cross-cultural considerations need to take into account including food beliefs and traditional food culture.16 In general, food intake

of Indonesian elderly in this study was quite healthful in that it was rich in grains, fruits, vegetables, and fish. It is almost in line with food intake habits of elderly southern Europeans which is rich in grain, vegetables, fruit, lean meat and olive oil.17

A study among French elderly also found that older subjects ate meat, fish, grains, raw vegetables and pulses less regularly.18 A study in Uganda also found similar patterns of food intake high in vegetables, legumes, nuts, and low in meat and animal fats.10 The Hertfordshire cohort study among the elderly found two dietary patterns, the first one characterized by high consumption of fruit, vegetables, oily fish and wholemeal grains; and the second pattern characterized by high consumption of vegetables, processed and red meat, fish and puddings.19

Intake of grains and cereal products were high among Indonesian elderly. High intake of cereal in Indonesian elderly was derived from the high intake of rice and rice noodles. Other common characteristics of Indonesian traditional cuisine is the use of coconut milk. It is used in recipes for savory dishes and desserts. Results in this study found that intake of coconut milk was higher in the elderly women. Compared to elderly men, elderly women had higher intake of eggs. Other study found that elderly consumed 10-15 g eggs which indicated that about one egg every 5 days.20

In comparison with previous studies conducted in Indonesia prior to the economic crisis, this study found the same food patterns which contain higher levels of plant proteins than animal proteins.13 This supports the theory that food patterns of Indonesian elderly have not changed despite the economic crisis.

Due to the variety of food choices among the elderly, eating-related difficulties may explain, at least in part, to inadequate intake of nutrients.21 Some studies have suggested that the effect of age on dietary habits may be attributable to functional impairments and chewing problems. These factors may lead elderly persons to have monotonous and energy-restricted diet, which easily results in an inadequate intake of nutrients.15 Social and economic conditions can adversely influence eating pattern and dietary


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choices.22

Based on the multivariate analysis results, we found that sex, education, and osteoporosis is significantly associated with energy intake. Elderly females were found to have energy intake of more than 80% RDA. This result was consistent with other study that found elderly females have higher energy percentage of RDA than males.23 Elderly with lower education levels were at risk of having energy intake less than 80% RDA. This result is consistent with the study conducted by Sharkey stating similar result.23

Other studies also indicate that level of education is associated with nutritional status which is the result of low energy intake.24 Higher level of education were more likely to be associated with higher income and better lifestyle, which will result in higher energy intake and better nutritional status in elderly.15

In this population, osteoporotic elderly more likely to have an energy intake more than 80% RDA. Further analysis showed that osteoporotic elderly had more intake of milk, eggs, and seafood which are rich sources of protein and calcium. These subjects consumed more amounts of protein and calcium in order to maintain bone health and prevent osteoporotic fractures. Protein and calcium are important elements of bones and several studies report that protein supplementation improves the medical outcome in elderly hip fracture patients.25-27 Osteoporotic elderly in this study also consumed more fruits than non-osteoporotic elderly. Fruit is an important source of potassium and magnesium that also have an important role in bone health.28,29

Limitations of the present study need to be pointed out such as the possibility of bias in obtaining information on chronic diseases which was based on self-reported interviews. The accuracy of such information differs according to the type of disease and the severity of symptoms. Data of food and nutrient intake was obtained by 24-hour food recall method, which could result in misreporting of food intake since the subject is elderly. Misreporting of self-reported food intake is an acknowledged source of measurement error in prospective or retrospective methods of dietary assessment.30 Other additional factors that contributed to the energy intake and nutritional

status such as poverty, poor quality of housing, poor access to health and social services, and food preparation were not assess in this study.

coNcluSIoN

The results of this study confirm that total energy intake including macro and micro nutrient were inadequate in the elderly. Female sex and osteoporotic subjects have lower risk for having <80% RDA daily energy intake, while lower educational level has higher risk for having <80% RDA daily energy intake. As this study is multicentre study and since the subjects came from geriatric clinic, the results of this study could be applied in elderly who come to geriatric clinic. It is important for government officials and health professionals to construct a national plan to promote health and nutrition of the elderly in order to ensure that elders have adequate intake and improve their nutritional status and quality of life. Nutritional counseling that recommends a balanced diet and adequate intake may help to maintain and/or improve the health status of the elderly.25 Family and social support for preparing food variations and balanced diet for the elderly is important. Assessment of eating behavior capacities is also needed to prevent inadequate intake and nutritional problems in the elderly.

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Profile of Food and Nutrient Intake Among Indonesian Elderly … · 2014. 2. 1. · 265 ORIGINAL ARTICLE Acta Medica Indonesiana - The Indonesian Journal of Internal Medicine Profile