Compar parison ison of Two Clinical ical Case Defini initio - PowerPoint PPT Presentation

Compar parison ison of Two Clinical ical Case Defini initio tions ns in Detecting cting Ov Overwe rweight ight and Ob Obesity ity Among ng Registere tered d Nurse ses s in A D District rict Speci cialist list Hospita pital Members: Teh Pei Nee 1 Chiew Shoen Chuen 2 Sheila Gopal Krishnan 3 Yap Ee Lee 4 Fauziah Yusof 5 Rasidah Abdul Manan 5 Mathavi Santhrasegaran 1 Roszimah bt Ismail 6 Hazira Abdul Kadir 7  1 Staff Nurse, Special Care Nursery, Hospital Seri Manjung  2 Pharmacist, Clinical Research Centre, Hospital Seri Manjung  3 Head of Paediatric Department, Hospital Seri Manjung  4 Nursing Sister, Paediatric Ward, Hospital Seri Manjung  5 Staff Nurse, Paediatric Ward, Hospital Seri Manjung  6 Staff Nurse, Intensive Care Unit, Hospital Seri Manjung  7 Staff Nurse, Psychiatric Clinic, Hospital Seri Manjung NMRR-16 16-766 766-28807 28807 1

AREA LAND : 1,168km² POPULATION : 247,603 ( 2015 ) 2

 The Manjung District is a district in the southwestern part of Perak state, Malaysia.  The district is well known for Pangkor Island, a major attraction in MANJUNG Perak and the home of the Royal Malaysian Navy (TLDM) Lumut Naval Base and dockyard. Bandar Seri Manjung is the district's principal urban center while smaller towns include Lumut , Sitiawan, Ayer Tawar, Pantai Remis and Beruas. 3

HOS OSPITAL PITAL SERI MANJUNG UNG 305 305 beds NAVI HOSPITAL 1 HOSPITAL DESA PANGKOR 1 PRIVATE HOSPITAL 2 GOVERMENT HEALTH CLINIC 31 PRIVATE HEALTH CLINIC 72 5

Departm rtmen ents ts Units ts • Medical • Haemodialysis Unit • Surgical • ICU / CCU • Orthopaedic • Physiotherapy Unit • Ophthalmology • Occupational • Emergency & Traumatology Rehabilitation • Paediatrics • Sterile Equipment Supply • Obstetrics & Gynaecology Unit • Psychiatry & Mental Health • Health Education Unit • Diagnostic & Imaging • Medical Social Work Unit • Pharmacy & Supply • Counselling Psychology • Pathology Department Unit • Dietetics & Catering • Quality Unit / Innovation & CRC (Clinical Research Centre) 6

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Health burden 8

 BMI = weight (kg) height (m 2 ) Overweight and obesity classification /m 2 ) Catego gory ry IBMI (kg/ g/m 2 ) ABMI (kg/m Underweight <18.50 <18.50 Normal 18.50-24.99 18.50-22.99 Overweight erweight 25.00 00-29. 9.99 99 23.00 00-27. 7.49 49 Obese ≥ 30.00 ≥ 27.50 Source: WHO 2004¹, CPG on Management of Obesity 2004². 9

3) There has been some contention whether the generalisation of the IBMI (International Body Mass Index) to the Asian population will underestimate the prevalence of overweight and obesity. 4) In year 2004, WHO was recommended additional BMI cut-off points for Asian populations for public health. (≥ 23 kg/m 2 as increased risk and ≥ 27.5 kg/m 2 as high risk). 10

5) BMI cut-off points have been revised to suit Asian population due to: (i) high prevalence of Type 2 Diabetes Mellitus among Asian individuals with BMI < 25.0kg/m 2 , (ii) higher cardiovascular risk factors among Asian individuals at any BMI level, and (iii) population based association between BMI, body fat percentage and distribution. 11

 Prevalence of overweight and obesity is Lamon-Fava va S et al, 1996 96 highest in developing countries and is Hossain in, 2007 07 associated with increase in incidence of Bhuro rosy et al , 2 2014 cardiovascular disease. Deure remberg erg-Ya Yap M et The BMI recommendation for public health was al, 2001 01 less than IBMI classification. (Singapore) ( ≥23 kg/m 2 as increased risk and ≥27.5 kg/m 2 as high risk) Feng ng R N N, et al 2 2012 The optimal BMI for men and women to predict (China) co-morbidities was less than IBMI classification. ( 24 kg/m 2 ) Ren n Q, et al 2 2016 16 The optimal BMI for men and women to predict (China) Hypertension was less than IBMI classification (23.53kg/m 2 and 24.25kg/m 2 ). Tanu, et al 2 2014 14 The optimal BMI to predict Hypertension was (India) ≥24.5 kg/m 2 (men) n) and ≥24.9 kg/m 2 ( women) n). 12

Bogossian ian FE e et al, The prevalence of overweight and obesity among 2012 12 nurses and midwives were higher compared to the general population in Australia, New Zealand and UK. Miller r SK et al, The prevalence of overweight, obesity and 2008 08 morbidly obesity among American nurses were 30%, 18.7% and 5.2% respectively. Ogunjim unjimi LO et al, The prevalence of obesity among Nigerian nurses 2010 10 62.6%. 13

Malaysia ian n National nal Healt lth h Increa rease of o obesit ity y preva valence lence from and Morbidity ty Surve vey 14 % (2006) 06) to 15.1% % (2011 011) (MNHMS) HMS) in local populati tion on aged above 18 years rs 2006, 06, 2011 11 Malaysia ian n National nal Healt lth h IBMI classification IBMI and Morbidity ty Surve vey, y, - overweight: 30.0% and obesity : 17.7% 7% 2015 15 ABMI classification – overweight: 33.4% 4% and obesity: 30.6%. %. WHO- Non Communicable Among obese population, female le Malays ysians ans • Disease Profile in Malaysia, were re more affecte cted than n the male 2012 counterparts Coomarasa asamy my JD e et al, The prevalence of overweight and obesity 2014 14 among female nurses in Malaysia were 33.5% % and 17.1% 1% respectively. 14

 This study endeavours to answer whether by using IBMI classification among Asian population would lead to a significant proportion of the overweight individuals going below the radar. Hypothesis : Are we missing a significant number of overweight nurses with associated comorbidities by using IBMI criteria? 15

General Objective  To compare the prevalence of overweight and obesity based on IBMI and ABMI among female registered nurses. Specific Objectives 1) To compare the prevalence of cardiovascular (CV) related co- morbidities among those who were overweight and obese according to both definitions. 2) To determine the factors associated with overweight and obesity in the study population. 16

Cross-sectional Study Hospital Seri Manjung Nurses in all departments September - October 2016  Sampl mple e size ze : 384 (minimum) : - Stratified random sampling (working schedule) - A random number list was generated by using Epical 2000 software. - Proportions were set at 50.6% and precision at 5% (45.6- 55.6%). MREC C approved 17

 Inclu clusion sion cri riteria teria : : All female registered nurses in HSM  Exclus clusion ion criter teria ia : Pregnant, on confinement / paid / unpaid leave, refuse to consent 18

 Data co collectio ection :  Demography, health, work environment, dietary, physical activity were collected via interview by trained researchers by using questionnaire.  Adapted from Canadian National Survey of the Work and Health of Nurses¹ ² , 2005  Data analysi ysis :  Prevalence of outcome was presented as %  Sensitivity & specificity of both definitions in predicting CV- related co-morbidities were calculated  Associating factors were analysed using multiple logistic regression MREC C approved 19

Consent taking process Measuring of height and weight as well as BMI calculation Interviewing the respondent by using questionnaire 20

Nurse ses who fulfill lled ed the inclus usion on criter teria ia were re give ven n Respond ondent nt Inform rmati ation on Sheet. Researchers archers explained ained to respon onde dents nts about t the study. . Respond ondents nts were given n sufficient cient time to understand tand, , ask questi tions ns and consid ider before re deciding iding on their r partici icipatio ation. n. All responde ondents nts were re asked d to sign n 2 sets of inform rmed consent nt form. Figure 2: Information sheet & Consent taking process 21

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Result 23

Table 1: Characteristics of Respondents* total respondents = 393 Characteri racteristic ics n n (%) Demographic Data Age in years, median (quartiles) 36 (32-41) Ethnicity Malay 361 (91.9%) Chinese 3 (0.8%) Indian 23 (5.9%) Others 6 (1.5 %) Marital Status 9 (2.3%) Single 378 (96.2%) Married 2 (0.5%) Divorced 4 (1.0%) Widow Body Mass Index (BMI) BMI in kg/m 2 , median (quartiles) 26.30 (23.63-30.13) Weight satisfaction 118 (30.0%) Satisfied 275 (70.0%) Not satisfied 24

IBMI ABMI MI No. & % of No. & % of Categor tegory Categor tegory respondents in respondents in CVD CVD each category 1 each category 1 (n, %) 2 (n, %) 2 Overwe rweight Overwe rweight 146 (37.2%) 7.2%) 21 (14.4%) 136 (34.6%) 4.6%) 14 (10.3%) (25-29 29.9kg/m 2 ) (23 23-27 27.49k 9kg/m 2 ) Obese se Obese se 102 (26.0%) 6.0%) 25 (24.5%) 172 (43.8%) 3.8%) 35 (20.3%) (≥ 30kg/m 2 ) (≥ 27.5kg/m 2 ) 1 : The denominator was total respondents (393)  2 : The denominator was respondents in the particular BMI category  CVD = cardiovascular disease  25