CARDIOVASCULAR RISK FACTORS AMONG STAFF IN PETALING HEALTH

OFFICE WORKPLACE, 2011

T Harishah1

,AS Ismail 1, Noriklil Bukhary IB

2,

Nazarudin Safian3,

1NCD Unit, Petaling District Health Office Selangor 1Ministry of

Health, Malaysia3Department of Community Health, UKM Medical Centre

Overview

1)Introduction

2)Methodology

3)Results

4)Discussion

5)Study Limitation

6)Conclusion

OVERVIEW

Cardiovascular diseases (CVD) main causes of

global preventable morbidity & mortality in

developing countries .

In 200116.6 million deaths worldwide, caused

by CVD & would increased 25 million by 2025

65% of worldwide deaths caused by CVD

occurred in developing countries mostly affect

people in age of 30-64 years .

Thomas A.Gazio. Reducing the growing burden of CVD in the developing world.

Health Affair. 2007;26(1): 13-24

INTRODUCTION

Vitro IB et al (2004) : CVD significantly

related to a number of risk factors (RF).

NHMS III 2006, ≥ 30 yo HPT (42.6%), DM

(14.9%), hypercholestrolaemia (26.9%),

overweight (29.1 %) & obesity (14.2 %)

significantly.

Chia Yook Chin & Srinivas Pengal (2009) to

measure CVD risks :Semirural Community,

Malaysia 55.8% men & 15.1% women ≥ 20%

risk CHD the next 10 years.

INTRODUCTION

Intermediate

Risk Factors

RISK FACTORS & DISEASES

Non-modifiable risk factors:

•Age

•Sex

•Ethnicity

•Genes

Modifiable risk factors:

•Diet - unhealthy

•Physical inactivity

•Tobacco use

•Alcohol

•Stress

Socioeconomic, cultural &

environmental determinants:

•Globalization

•Urbanization

Obesity/Overweight

Raised blood pressure

Raised blood glucose

Abnormal blood lipidsDiabetes

Cancers

Lung Disease

ED (Erectile

Dysfunction)

stroke

Heart Disease

END POINT

RATIONALE AND OBJECTIVE

One of the 7 strategies in National

Strategic Plan for NCD1M (2010-2014)

awareness of Malaysians on total CVD

risks.

A few published studies in Malaysia on CVD

risk among health care workers

The objectives:

to determine the prevalence of

CVD risk factors among

respondents.

to measure CVD risk using the

Framingham Coronary Disease

Risk Prediction score (FRS)

among respondents

STUDY BACKGROUND

Conducted among staff in PKD Petaling

with sample population 626 staff from 17

Dec-15 Jan 2011

STUDY DESIGN: Cross sectional study

SAMPLING METHOD:Universal sampling.

METHODOLOGY

SAMPLING METHOD

612

Aged 18-58

454 interviewed (72.5%)

158

EXCLUDED

-15 staff were

pregnant

-147 staff

refused to join

the CVD

screening.

-10 staff were

excluded in this

study due to

incomplete

information

excluded

RESEARCH INSTRUMENTS:

Standardized self administered

questionnaire-simplified from MyNCD

Survey 2005/2006.

Blood pressure (BP)

Body Mass Index (BMI)-Weight & height

Waist Circumference (WC)

Fasting plasma glucose (FPG)

Fasting serum lipid (FSL)

METHODOLOGY

DEFINITION:

All the variables follow the MyNCD 2005/2006

STATISTICAL ANALYSIS:

SPSS version 15

Univariate analysis: Frequency Distribution

METHODOLOGY

RESULTS &

DISCUSSIONS

Table 2 The Cardiovascular Risk Factors among Petaling Health staff

2011 (N=454)

CVD Risk Parameter

Prevalence (%)

All (N= 454) Males (n=136 ) Female(n=318)

Overweight/obese 247(54.4) 78 (57.3) 169(53.1)

Overweight 155(34.1) 52(38.2) 103(32.4)

Obese 92(20.3) 26(19.1) 66(20.7)

Central Obesity 246 (54.2) 72(52.9) 174(54.7)

Raised Blood Sugar 80(17.6) 49(36.0) 31(9.7)

Known cases 36(7.9) 17(12.5) 19(6.0)

FPG≥ 7mmol/L 44 (9.7) 32(23.5) 12(3.8)

Raised Blood Pressure 54(11.8) 31(22.8) 23(7.2)

Known cases 24(5.3) 10(7.4) 14(4.4)

High BP 30 (6.6) 21(15.4) 9(2.8)

Current smoker 49(10.8) 49(36.0) -

T. Chol > 5.2 mmol/L 199(43.8) 64(47.0) 135(42.4)

HDL –chol < 0.9 mmol/L 30(6.6) 19(14.0) 11(3.5)

Table 1 :Comparison social demographic status - NCD & Petaling

Petaling 2011

( n=454)

n %

age Median IQR (30.0)

<25 63 13.9

25-34 271 59.7

35-44 61 13.4

45-54 47 10.4

55-64 12 2.6

gender

Male 136 30.0

Female 318 70.0

Ethnicity

Malay 395 87.0

Chinese 15 3.3

Indian 39 8.6

Others 5 1.1

NCD 2006 (n=2572)

n %

- -

610 23.7

738 28.7

747 29.0

477 18.5

1044 40.6

1528 59.4

1425 55.4

461 17.9

231 9.0

455 17.7

Table 5 Comparison CVD risk factors(%) between NCD survey 2006

(N= 2572), NHMSIII(N=34,539) with Petaling Health staff 2011(N=391)

010203040506070

Raise

d BP

Raise

d BG

Hype

rcho

lest

erol

e…

over

wei

ght/

obes

ity

Cent

ral O

besit

y

Curre

nt sm

oker

Petaling 2011

NCD 2006

NHMS111

PREVELENCE OF RAISED BLOOD GLUCOSE

PETALING 2011

NCD SURVEY

NHMS 111(34,539)

RAISED BLOOD GLUCOSE

14.6% 11.0% 11.5%

•KNOWN CASES

8.4% 4.5% 7.0

•NEW CASES

6.5% 4.5

Letchuman et al (2010)Malaysian’s diet rich in fat and

carbohydrates. As Malaysia now is toward urbanization &

sedentary lifestyle, these will increase the prevalence of DM

PREVALENCE OF OVERWEIGHT/OBESITY

STUDIES

Petaling

2011

Acevedo M A et

al 2011

CVD Risk factors

among a university

hospital health

workers population

in Santiago , Chile

Harian Metro

2009

-Datuk Seri Liow Tiong

Lai

overweight/obese health

care staff : 60% which is

nearly the same as in the

community

NCD2006

NHMSIII

Prevalence

54.4% 58% 60% 47.9 43.1

DISCUSSION

Prevalence of overweight/obese

Prevalence of overweight/obesity & central

obesity in this study almost the same, 57.8% &

57.3 % nearly 10 % compared with NCD 2006

within 5 years.

Majority of age in this study between 25-34, the

BMI ≥ 25 kg/m2& central obesity affect the

young age.

Table 4 Comparison of intermediate risk factors* in

percentage between NCD Survey 2006 and Petaling

Survey 2011

Petaling Survey

2011

NCD 2006 (n= 2572)

Number

of risk

factors*

Frequen

cy (n)

Percen

t (%)

Frequency

(n)

Percent (%)

0 141 36.1 813 31.6

1 165 42.2 1006 39.1

2 57 14.6 545 21.2

3 24 6.1 180 7.0

4 4 1.0 28 1.1

total 391 100 2572 100

*The intermediate risk factors include raised blood pressure,

raised blood glucose, hypercholestrolaemia and obesity

21.7% 28.3%

Table 3 Distribution of CVD risk for age ≥30 years

old using Framingham Risk score among Petaling

Health Staff (N=242)

CVD Risk Male Female All

n (%) n (%) n (%)

Low 48(21.5). 175(78.5) 223 (96.2%)

Intermediate 7(63.6) 4(36.4) 11(4.5%)

High 7(87.5) 1(12.5) 8(3.3%)

Total 62(25.6) 180(74.4) 242(100)

Wan Rosealaiza WAG et al.

Kajian Prevalen Dan Faktor Risiko Kardiovaskular Di Kalangan

Kakitangan Kesihatan Di Daerah Bera, Pahang 2009 (281 responden

(83.9%), median age 30.0

2.1% High risk,

5.7 % intermediate risk 10-20%

92.2% low risk.

High risk ≥ 20%, intermediate risk 10-20% and low risk < 10%

Overview

Petaling

2011

-low CHD risk (92.2%),Intermediate (4.5%) ,High

(3.3%).

-Among the high CHD risk (≥ 20%), 87.5% were

men

Chia

Yook

Chin

(2009)

55.8% of the men had ≥20 % risk

women’s risk was lower, with 15.1 % having a risk

of ≥ 20%.

(Mean age: 65.4 years (±8))

DISCUSSION

Using the Framingham 10 year CHD risk

prediction score

DISCUSSION

Hypercholestrolaemia

higher in NCD (53.5 %) compared to Petaling

survey (46.5 %)

Gostynski M et al (2004):

Analysis of relationship between cholestrol and

age Hypercholestrolaemia increased with age

DISCUSSION

Smoking

Petaling survey. Among 391 respondents with

age ≥ 25, 9.2% were smoker. This figure was

lower than NCD survey with was 25.5%.

This might be due to the male ratio were 1:3 in

Petaling survey, meanwhile in NCD survey the

male ratio were 2:3. Under reported or their work

place discourage them to smoke.

Rampal et al (2006) smoking was associated

with race, age, sex, educational level and peer &

family influence.

LIMITATIONS

Temporal relationship could not be assessed in cross

sectional study.

High BP at the first time should be repeated with other

period of time & high glucose should be confirmed

with 2 hours post-prandial glucose.

Respondents work in health department difference

type of working categories (medical and non-medical)

& difference level of education that should be

addressed.

Those refused to participate should also be analysed

INTERVENSI OBESITY PROGRAMJANUARY 2011

Jumlah peserta disaring 457

Jumlah peserta yang didaftarkan di

dalam web based 457

Jumlah peserta yang setuju untuk

diintervensi 40

% 'Retention Rate' selepas 6 bulan

intervensi 100.00%

RINGKASAN PESERTA INTERVENSI

Comparison of BMI Disember 2010 and Julai 2011

% Klien yang berjaya menurunkan berat badan

(KPI TKPKKA) 7/40(17%)

% Klien yang berjaya menurunkan berat badan

sekurang-kurangnya 10% dari berat badan asal

(initial body weight)

0%

Comparison of Fasting Blood Sugar Disember 2010 and Julai 2011

a. Borderline diabetes - % berjaya kembali ke

paras normal 11/25 (44 %)

b. Borderline diabetes - % kekal borderline 14/25(56%)

ada 4 kes yang berubah dari group 1 jadi 2

c. Borderline HPT - % berjaya kembali

ke paras normal 4/10(40%)

d. Borderline HPT - % kekal borderline 4/10(40%)

1 kes dari grp 2 ke 3 1 kes dari grp 2 ke 3

e. Hiperkolesterolemia - % berjaya

kembali ke paras normal 10/21

CONCLUSION

The prevalence of raised blood glucose,

overweight, obesity and central obesity were

higher compared to NCDS 2006 & the trend

currently shifting to youngsters.

All health care workers need to be screen for

CVD risks urgently.

Well structured and monitored NCD risk

factors intervention program is needed in

order to control and prevent NCD morbidity

and mortality among health staff.

THANK YOU

REFERENCES

• IC-Health. Public Health at Glance-Cardiovascular health at glance. 2003. [cited 2011 March12] Available from: http://www.ichealth.org.

• Thomas A, Gazio. Reducing the growing burden of cardiovascular disease in the developingworld. Health Affair. 2007; 26(1):13-24

• Khoo KL, Tan H, Liew YM. Serum lipids and their relationship with other coronary risk factorsin health subjects in a city clinic. Medical Journal of Malaysia. 1997; 52: 38-52.

• Mohd Yunus, Sherina MS, Nor Afiah MZ, Rampal L, Tiew KH. Prevalence of cardiovascular riskfactors in a rural community in Mukim Dengkil, Selangor. Malaysia Journal Nutrition.2004; 10(1): 5-11.

• Robaayah Zambahari. Trends in cardiovascular diseases and risk factors in Malaysia, NationalHeart Institute. Kuala Lumpur .2004

• Vitro IB. Control and prevention of cardiovascular disease around the world. Res Esp Cardiol.2004; 57(6):487-94.

• D’Agostino RB, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM. et al. Generalcardiovascular risk profile for use in primary care:The Framingham Heart Study. Journal ofAmerican Heart Association. 2008; 117:743-753.

• Lindholm LH, Ekbom T, Dash C, Eriksson M, Tibblin G, Schersten B. The impact of health careadvice given in primary care on cardiovascular risk. British Medical Journal. 1995; 310:1105-9.

• Wilson PW, D’Agostino RB, Levy Daniel, Belanger AM, Halit Silbershatz, Kannel WB. Predictionof coronary heart disease using risk factor categories. Circulation.1998; 97:1837-47.

• Abdesslam Boutayeb, Saber Boutayeb. The burden of non communicable diseases indeveloping countries. International Journal for Equity in Health.2005; 4(2):1-8.

REFERENCES

• Chia Yook Chin, Srinivas Pengal. Cardiovascular Diseases Risk in a Semirural Community in Malaysia. Asia Pacific Journal of public Health. 2009 ; 21 (4):410-19.

• Ministry of Health. Malaysia Non-Communicable Disease Survey (MyNCDS-1) 2005-2006: NCD Risk Factors in Malaysia. Noncommunicable Disease Section, Disease Control Division. 2006.

• Zalilah, Khor GL, Mirnalimi K, Norimah AK, Ang M. Dietary intake, physical activity and energy expenditure of Malaysian adolescents. Singapore Medical Journal. 2006; 47(6):491.

• Institute for Public Health. The Third National Health and Morbidity Survey 2006 (NHMS III): Executive summary: Institute for Public Health, National Institutes of Health, Ministry of Health. 2008.

• World Health Organization. Obesity: Preventing and managing the global epidemic. Report on a WHO Consultation. Geneva; 2000.

• WHO. Obesity and Overweight.World Health Report. 2011.[cited 2011 March15]. Available from:http://www.who.int/media.centre/factsheets/fs311/en/

• WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004; 363:157-63.

• Bell AC, Swinburn BA, Amosa H, Scragg RK. A nutrition and exercise intervention program for controlling weight in Samoan communities in New Zealand. International journal of Obesity;2001.25:920-27.

• Ministry of Health, Academy of Medicine of Malaysia & Malaysian Society of Hypertension Clinical Practice Guidelines Management of Hypertension .3rd edition. 2008.

Surprisingly, BP that high during screening were

almost the same amount of % for the known

case in both group studies.

Due to white coat hypertension phenomena &

it needs to be clarify with further follow-up.

Table I: Status of Diabetes Mellitus and Impaired Glucose Tolerance (IGT) / Fasting Glucose (IFG) (%) in Malaysia in the past 20 years

1996 2006

Age groups >=35 >= 30 > 18 >= 18-< 30 >= 30

Diabetes Prevalence (%)

6.3 8.3 11.6 2.4 14.9

Known diabetes (%)

4.5 6.5 7.0 0.4 9.5

Newly diagnosed (%)

1.8 1.8 4.5 2.0 5.4

IGT / IFG (%) *4.8 *4.3 #4.2 #3.1 #

Overview

Petaling

2011

0-1 intermediate risk factors 78.3 %

Two or > risks factor 21.7%.

the distribution of age in Petaling survey were

more to younger age.

NCD 2006 0-1 intermediate risk factors 70.7%

Two or > risks factor 28.3%.

DISCUSSION

Comparison of intermediate risk factors

The risks would if it combined with other variables.

Overview

• In Petaling, the prevalence of known cases of

HPT & diabetes- 5.3% & 7.9%, respectively.

• These findings were differed from Human

Resource Management (2007)-out of 73 579

among health care staff, 7.5% were HPT & 4

% were diabetes .

DISCUSSION