Lipid Profiles Among Diverse Ethnic Groups in Indonesia

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ORIGINAL ARICLE

Acta Medica Indonesiana - Te Indonesian Journal of Internal Medicine

Insulin Resistance as One of Indicators for Metabolic

Syndrome and Its Associated Factors in Indonesian Elderly

Arya G. Roosheroe, Siti Setiati, Rahmi Istanti

Department of Internal Medicine, Faculty of Medicine, University of Indonesia Cipto Mangunkusumo Hospital.Jl. Diponegoro no. 71, Jakarta Pusat 10430, Indonesia. Correspondence mail: [email protected]

ABSTRAK

Tujuan:mendapatkan faktor-faktor yang berhubungan dengan resistensi insulin pada usia lanjut di Indonesia.

Metode: penelitian dengan disain cross sectional dilakukan di Poliklinik Usia Lanjut RSCM Jakarta dengan jumlah

sampel 172 usia lanjut. Data yang dikumpulkan meliputi karakteristik subyek (usia, jenis kelamin), indeks massatubuh, lemak tubuh total, lemak subkutan perifer, lemak subkutan trunkal, lingkar pinggang, asupan karbohidrat

dan serat, aktivitas sik, dan konsentrasi 25(OH)D. Besar sampel dihitung dengan rumus besar sample untuk uji

hipotesis beda 2 proporsi dan untuk uji hipotesis beda rerata pada 2 kelompok independent. Tingkat kepercayaan

yang digunakan 95% dan kekuatan uji 80%. Analisis chisquare dan t-test independent digunakan sebagai analisis

bivariat. Analisis statistik regresi logistik digunakan untuk melihat variabel yang paling mempengaruhi resistensi

insulin. Batas kemaknaan yang digunakan adalah p


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INTRODUCTION

As the number of elderly population in

Indonesia is increasing, various health problems

related to the age group will also be increasing.

The common elderly health problems arechronic degenerative diseases such as diabetes

mellitus, hypertension, dyslipidemia, obesity,

and cardiovascular disease. The existence of

insulin resistance in elderly is associated with

the development of those diseases.1

Insulin resistance is a condition when a

normal concentration of insulin inadequately

produces normal insulin biological response in

lipid, muscle and liver cells. Prevalence of insulin

resistance in elderly is approximately 40%.2

Factors suspected to cause insulin resistance in

elderly are anthropometric changes, especially

decrease of muscle mass accompanied with the

increase of body fat (particularly the visceral

fat), the decrease of physical activity, hormonal

changes, high carbohydrates and low fat intake.3

Vitamin D deciency is also suspected to be

correlated to the condition of insulin resistance.4

The prevalence of vitamin D deciency in elderly

is relatively high. A study conducted by Setiati

in Indonesian elderly women found that the

prevalence of vitamin D deciency is 35.1%.5

Metabolic syndrome is a condition in whichthere are three or more risk factors (low HDL

cholesterol, hypertriglyceridemia, obesity,

hypertension, and hyperglycemia). Insulin

resistance is associated with the condition of

metabolic syndrome. Body mass index as the

indicator of obesity was found to be correlated

to insulin resistance events.6 In elderly, changes

in intra-abdominal fat or visceral adipose tissue

and liver fat tissue are signicantly correlated to

the development of insulin resistance.3

Correlation between high carbohydrateintake and the incidence of insulin resistance

is still vague; some data suggest that high

carbohydrate intake has no effect to the incidence

of insulin resistance compared to high fat intake.7

In elderly, there is an overall reduced food intake,

which is accompanied with higher carbohydrate

intake. It has been demonstrated that calorie

restriction has a good effect on preventing altered

insulin performance in elderly. It may occur due

to reduced accumulation of visceral fat and lower

concentration of free fatty acid.

8

Physical exercise increases glucose

metabolism and prevents the development

of insulin resistance in elderly; however, the

mechanism has not been known. Studies on

obesity in elderly have revealed that visceral fat

is reduced after performing physical exercise

and glucose metabolism is increased and it is

correlated to prevention of insulin resistance.9

Studies about insulin resistance in elderly

are quite rare in Indonesia. There are differences

on body fat changes and body mass index in

Indonesian elderly compared to the elderly of

other countries. Moreover, the food composition

in Indonesian elderly has higher carbohydrates

intake compared to the ber intake and there

is also a relatively high prevalence of vitamin

D deficiency in Indonesian elderly, which

encouraged us to conduct a study to nd out

which factors that may affect insulin resistancein Indonesian elderly.

METHODS

A cross sectional study was conducted at

the Geriatric Outpatient Clinic, Department

of Internal Medicine, Faculty of Medicine,

University of Indonesia, Cipto Mangunkusumo

hospital between August 2009 and May 2010.

The study population included all elderly patients

who had their treatment at the study site. The

inclusion criteria were elderly patients aged 60

years or more, and willing to participate in the

study. Subjects with chronic kidney disease, liver

chronic disease, and pre-existing medication

of dyslipidemia, corticosteroid, beta-blocker

and thiazide were excluded. Sample size was

calculated in accordance with the formula of

sample size on hypothesis testing for difference

of two proportions and hypothesis testing for

difference of mean of two independent groups.

Significance level of 95% and 80% power

were used. Data collected including subjectscharacteristics (age, sex), anthropometric

characteristics (BMI, total body fat, peripheral

subcutaneous fat, trunk subcutaneous fat,

and waist circumference), carbohydrate and

fiber intake, physical activity, and 25(OH)D

concentration.

Measurement Methods

Body weight was measured using the

standing weight scale. Subjects were measured in

standing position with minimal clothes, emptiedpocket and bare-footed. The measurement was

read on the weight scale with precision up to 0.1


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kg. Knee height was measured with knee-height

measurement tool. Subjects were measured in

supine position, of the left leg, with tibia and

femur angled to 90o, the tool was positioned

between heels and until the proximal part to

patella bone. Waist circumference was measured

using caliper on abdominal area across midline

of lowest inferior costae and iliac bone. The

measuring tape is positioned as appropriately

as possible in a horizontal plane. Subjects were

measured in standing position with both feet

20-25 cm apart. Total body fat was measured

using Bioelectrical Impedance Analysis (BIA)

tool. Subjects were measured in supine position,

without pillow, normal clothing and without

wearing any metal objects. Four electrodes

would be attached to subjects, one in each wristand dorsum of right hand, ankle and dorsum of

right foot. The obtained results were body fat

percentage (%) and fat mass (kg).

Peripheral and trunk subcutaneous fat were

obtained by measuring 5 regions, i.e. peripheral

subcutaneous fat was measured in triceps

and thigh region; while trunk subcutaneous

fat was measured in subscapular, suprailiac

and abdominal region. Insulin resistance

was calculated based on HOMA-IR formula.

Carbohydrate and ber intake were collected bytaking interview on nutritional history using 24-

hour food recall method. The interview results

were processed further using the Nutrisurvey

program to obtain the values of carbohydrate

and ber intake. Physical activity was measured

using the six minute walking test.

Data Analysis

Data were analyzed with stata program

version 10.0. Bivariate analysis was performed to

evaluate the correlation between independent and

dependent variables. Analysis using Chi-Square

statistical test was conducted for ordinal scale

data and independent t-test was used for ratio-

scale data. Multivariate analysis was performed

to evaluate which independent variables have the

most signicant effects on dependent variables.

The analysis was conducted using logistic

regression statistical test. Signicance level of p

< 0.05 was applied.

RESULTS

There were 172 elderly subjects participating

in the study, with mean age of 71 years, ranging

from 60-88 years. More than half of subjects

(70.35%) were female. Subject characteristics

are shown on Table 1.

Table 1. Subject characteristics

Characteristics n (%)

Sex

- Male 51 (29.65%)

- Female 121 70.35%)

Age

- 60-70 years 82 (47.67)

- > 70 years 90 (52.33)

Nutritional status

- Underweight ( 25 kg/m2) 52 (30.23)

Carbohydrate intake

- Less (< 80% needs) 51 (29.65)

- Adequate (80-100% needs) 37 (21.51)

- Excessive (> 100% needs) 84 (48.84)

Fiber intake

- Less ( 100% needs) 14 (8.14)

Insulin resistance

- No 129 (75.00)

- Yes 43 (25.00)

Mean values of some numerical variables are

shown on Table 2.

Results of bivariate analysis using Chi-square

test showed the association between insulin

resistance and the affecting factors as shown

on Table 3. We found that the variables such

as age (OR 0.44; 95% CI 0.22-0.89) and body

mass index (OR 4.58; 95% CI 2.08-10.09) weresignicantly associated to insulin resistance.

The results of mean difference analysis using

unpaired t-test, which demonstrated the mean

differences of numeric variables between subjects

with insulin resistance and those without insulin

resistance, are shown on Table 4. We found

signicantly higher mean values (p0.05).


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The results of logistic regression analysis

(Table 5) indicated that only the variables of

trunk and peripheral subcutaneous fat were

significantly affecting insulin resistance in

elderly, with OR 1.09 (95% CI 1.05-1.15) and

OR 0.93 (95% CI 0.87-0.99), respectively.

DISCUSSION

In our study, the number of elderly subjects

with nutritional status of overweight and obesity

were more prevalent than underweight subjects.

The phenomena might be caused by nutritional

transition in Indonesia. As a developing country,

Indonesia has quite dramatic changes in age-

population structures, accompanied with changes

in dietary style, habit and physical activity. As a

result, this will cause increased risk of obesity and

chronic disease. Altered dietary habit includes

diet changes from high ber and low fat diet to

high fat, high carbohydrate and low ber diet.

Table 2. Mean values of body mass index, fat mass, fat thickness, waist circumference, physical activity, intake, and HOMA-IR

Variables Mean (sd) Min Max

Body mass index 23.09 (0.19) 12.46 39.42

Fat mass (%) 29.61 (10.06) 3.00 65.8

Fat mass (Kg) 17.16(1.17) 0.39 84.00

Fat thickness beneath triceps skin 19.94 (5.45) 4.00 36.00

Fat thickness beneath thigh skin 17.29 (4.35) 6.00 30.00

Fat thickness beneath subscapular skin 17.45 (5.34) 5.00 31.50

Fat thickness beneath suprailiac skin 20.98 (5.63) 5.00 35.00

Fat thickness beneath abdominal skin 26.00 (5.99) 7.50 45.00

Peripheral subcutaneous fat thickness 37,24 (9.54) 10.00 65.00

Trunk subcutaneous fat thickness 64.43 (15,61) 17.50 107.00

Waist circumference 84.59 (11.22) 57.5 118.00

Physical activity 4.55 (1.78) -0.40 8.70

Carbohydrate intake 237.75 (74.81) 7.14 435.13

Fiber intake 21.92 (33.89) 2.17 275.14

HOMA-IR 1.32 (2.53) 0.26 28.50

Table 3.Association between age, body mass index, 25(OH)D concentration, carbohydrate intake, fber intake and insulin

resistance

VariablesInsulin Resistance

OR (95% CI) pYes n (%) No n (%)

Age

- >70 years 16 (37.21) 74 (57.36) 0.44 0.024

- 60-70 years 27 (62.79) 55 (42.64) (0.22 0.89)

Body mass index

- Overweight-obesity 33 (76.74) 54 (41.86) 4.58 0.000

- Underweight -normal 10 (23.26) 75 (58.14) (2.08 10.09)

25(OH)D concentration

- Defciency (50) 4 (9.30) 15 (11.63) (0.40 4.09)

Carbohydrate intake

- >100% needs 20 (46.51) 64 (49.61) 0.78 0.73

-


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Moreover, we also found that the majority of

subjects (48.84%) consumed carbohydrates

more than 100% nutritional requirements and

83.7% subjects had low ber intake, 80% less

than required.

Total body fat, subcutaneous fat in triceps,

subscapular, suprailiac, abdomen and peripheral

fat found in our study is almost similar to those

values reported by Dwimartutie, in her study of55 outpatient elderly. However, BMI, abdominal

and trunk subcutaneous fat found in this study

is much higher.11 HOMA-IR concentration

value in our study was not normal, therefore, a

transformation was conducted. We found that the

mean value of HOMA-IR was 1.32. This value

is lower than those values reported by Motta,

which were 1.66 for 1549 elderly, and Kurniadhi,

who reported the value of 1.71 for 110 elderly

subjects.12-14

The condition of insulin resistance in ourstudy was diagnosed based on HOMA-IR >75

percentile study population, and the value was

2.67. This value is comparable to the value

found by Nasution in her study with 92 elderly

women in nursing homes in Jakarta.15 In addition,

another study reported lower HOMA-IR value

for insulin resistance, which was 2.48.

19

A studyconducted by Lee, et al with 976 subjects aged

30-79 years old in Korea reported a comparable

HOMA-IR cut-off limit for insulin resistance,

which was 2.34.14 The differences in HOMA-IR

cut off limit to diagnose insulin resistance, which

may be different among various populations

might be affected by sex, differences in body fat

distribution, age, and race (ethnicity).

The prevalence of insulin resistance in our

study was 25%. A study conducted by Nasution

also found similar prevalence of insulin resistance

(25%).15 The prevalence of insulin resistance

was increasing with age.15,16 The increase of

prevalence reached its peak by the age of 80

years and followed by decreased prevalence.16

Botnia et al. found increased insulin resistance

in older subjects.22

It has been reported that insulin resistance

increased with age. The results of bivariate

analysis in our study showed significant

association between age and insulin resistance

(p


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with BMI. In particular, To be more specic,

intra-abdominal and visceral fat were reported

to be associated with metabolic disorder and

insulin resistance. The results of bivariate

analysis in our study showed a significant

association between body mass index and

insulin resistance (p0.05). The OR value on

ber intake indicated a protective factor against

insulin resistance, although it was not statistically

signicant. A cross-sectional study with 2834

subjects aged 50 years or older did not nd anyassociation between total carbohydrate intake and

insulin resistance; however, a negative correlation

between insulin resistance and ber intake was

reported.25 Other observational studies also did

not nd any association between carbohydrate

intake and insulin, as well as the risk of diabetes

mellitus.26,27

Data of dietary intake in our study was

obtained using 24-hour food recall. There was

no association between intake and insulin

resistance in our study, which might occurbecause the method of nutritional assessment

was inadequate to represent the overall dietary

intake in elderly as it only evaluated 1-day dietary

intake. There might be a recall bias in elderly

subjects; therefore, we preferred the 24-hour

recall methods. However, 3 x 24 hour recall

methods or semi quantitative food frequency

is quite inapplicable for elderly due to memory

decit in this age group.

The role of physical activity in glucose

metabolism has been widely acknowledged.

A study conducted by Bianchi in 1144 elderly

subjects reported a reverse correlation between


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physical activity and insulin resistance.28 Another

study reported a protective effect of physical

activity against insulin resistance. Resistance

exercise will increase muscle mass, increase

glucose intake per muscle mass unit, and

signicantly increase insulin activity in skeletal

muscle.29

In our study, physical activity was measured

using six minute walking test. The results of

bivariate analysis did not show significant

difference regarding mean physical activity score

in metz between subjects with insulin resistance

and those without insulin resistance (p>0.05).

The absent of such difference may occur since the

measurement method, six minute walking test,

may not represent the actual activity of elderly.

Exercise in elderly will increase glucosemetabolism and prevents insulin resistance;

however, the mechanism is still unclear. In

elderly, aerobic exercise has been known to

increase functional capacity and decrease

diabetes risk. In addition, elderly individuals are

able to adapt to exercise increment, which may

lead to improved insulin performance.3

It has been said that the risk of diabetes and

insulin resistance increased with higher body

fat, which is calculated by using the body mass

index. Although the correlation is associatedwith the measurement of total body fat tissue,

which is measured by BMI, but some studies also

show that not all fat tissue contributes equally

in increased diabetes risk. Central fat depot,

i.e. intra-abdominal or visceral fat, including

mesenteric and intra-abdominal omentum,

has greater association with insulin resistance

compared to peripheral fat depot, such as gluteal

or subcutaneous fat or total body fat.30 The

results of bivariate analysis found that there

were signicant mean differences in all bodyfat variable (p


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Documents

Lipid Profiles Among Diverse Ethnic Groups in Indonesia