Latha Sathiyamoorthy Mentor Dr Kern May 7 th 2013.
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Transcript of Latha Sathiyamoorthy Mentor Dr Kern May 7 th 2013.
PLACE OF LIVING INFLUENCES PHYSICAL ACTIVITY, BMI, NUTRIENT INTAKE OF ASIAN INDIANS
Latha SathiyamoorthyMentor Dr KernMay 7th 2013
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ACKNOWLEDGEMENTS
My sincere thanks to Dr. Mark Kern Dr. Lalitha Ramaswamy Dr. Susan Levy All study participants Aarti Sachdeva Alex Zawilski Carly Sullivan Family
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BACKGROUND: ASIAN INDIANS IN USA
2000 20100
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
1,718,778
2,918,807
USA Asian Indian population
69.8%
2000 20100
100,000
200,000
300,000
400,000
500,000
600,000
360,392
528,176
California Asian Indian population
2000 20100
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
20,000
7,926
17,255
San Diego Asian Indian population
46.6%
117.7%
Fig 1 Fig 2
Fig 3 U.S Census Bureau, 2010.
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BACKGROUND: LEADING CAUSE OF MORTALITY AMONG AI IN CALIFORNIA
death per 100,000 No of death death per 100,000 No of deathAge 45-64 Age >=65
0
200
400
600
800
1000
1200
1400
83
154
875
491
205
476
1233
627
Death due to cardiovascular
FemaleMale
Palaniappan et al. 2010
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SOARING COST OF CVD
www.cdc.gov 2011
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PURPOSE
No studies examined and compared the influence of place of living on PA, BMI and nutrient intake among the Asian Indians.
Examine the PA, BMI and nutrient intake of Asian Indians living in San Diego and compare with those living in Coimbatore (South India)
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HYPOTHESIS
Asian Indians in San Diego compared to their counterparts in Coimbatore will
be more physically active have higher BMI have higher energy intake have greater nutrient intake
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METHODS
32 participants, male (N=16) female (N=16)
Age group of 18 -60 years 15 San Diego, male (N=7) female (N=8) 17 Coimbatore, male (N=9) female
(N=8) Inclusion and exclusion criteria Convenience non-random sampling
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METHODS
Single 24-hr diet recall Self-reported International Physical
Activity Questionnaire (IPAQ) Demographic questionnaire
self-reported height, weight, age, income, health info
BMI calculated (kg/m²)1kg=2.2 lbs
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METHODS
BMI category Under weight = <18.4 Normal weight = 18.5 to 22.9 Over weight = 23 to 24.9 Obese = >25 WHO
2000,2003, 2004
PA- METs (mins/week) was calculated Craig
et al., 2005;2004
Nutrient analysis- Food Processor (SD) and AuroNutriSoft (Coimbatore)
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METHODS
Participants from San Diego (SD) were grouped as living ≤ 10 yrs and > 10 years.
Descriptive statistics [Mean ± Std Dev; frequencies(%)] for demographic variables
Separate One-way ANOVAs (SPSS) were conducted to examine the differences in PA, BMI and nutrient intake of Asian Indians living in San Diego and in Coimbatore.
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RESULTS AND DISCUSSION
*data is presented as Mean± SD OR Frequency (percentage)
Table 1 Baseline characteristics of subjects based on place of living*Characteristics Total (N=32) San Diego (N=15) Coimbatore (N=17)
Age (Years) 38.19±12.31 38.87±10.11 37.59±14.27 Gender Male 16 (50) 7 (46.7) 9 (52.9)Female 16 (50) 8 (53.3) 8 (47.1)Marital status Married 24 (75) 14 (93.3) 10 (58.8)Unmarried 8 (25) 1 (6.7) 7 (41.2)Education qualifications Doctorates/Professional 2 (6.2) - 2 (11.8)Postgraduate 17 (53.1) 11 (73.3) 6 (35.3)Bachelors 8 (25) 2 (13.3) 6 (35.3)Associate degree 2 (6.2) 1 (6.7) 1 (5.9)High school 2 (6.2) 1 (6.7) 1 (5.9)Middle school 1 (3.1) - 1 (5.9)Employment Executives 3 (9.4) 2 (13.3) 1 (5.9)Doctor 1 (3.1) - 1 (5.9)Engineer 10 (31.3) 7 (46.7) 3 (17.6)Small bus 7 (21.9) - 7 (41.2)Others 11 (34.4) 6 (40) 5 (29.4)
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RESULTS & DISCUSSION CONT’DTable 1 cont'd
Characteristics Total (N=32) San Diego (N=15) Coimbatore (N=17)
Annual household income ($) >$150,000 5 (33.3) $100,000-150,000 5 (33.3) $70,000-100,000 3 (20) $40,000-70,000 2 (13.3) $10,000-40,000 - Income (₹)a >₹. 20,00,000 2 (11.8)₹. 10,00,000 -20,00,000 -₹. 5,00,000-10,00,000 5 (29.4)₹.2,00,000-5,00,000 3 (17.6)<₹. 2,00,000 7 (41.2)Height (cm) 165.10±9.80 167.28±9.71 163.18±9.76Weight (kg) 65.03±10.74 70.00±7.39 60.65±11.49BMI Category <18.4 –underweight 3 (9.4) - 3(17.6)18.5-22.9 –normal weight 11 (34.4) 3 (20) 8(47.1)23-24.9 –overweight 5 (15.6) 4 (26.7) 1 (5.9)>25 –obese 13 (40.6) 8 (53.3) 5 (29.4)*data is presented as Mean± SD OR Frequency (percentage) a values expressed in rupees (Indian currency)
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RESULTS AND DISCUSSION CONT’D
Variables San Diego (N=15) Coimbatore(N=17) p-value
BMI 25.0±2.3 22.9±5.0 0.149METs minutes/ week 2479±2124 3452±2344 0.230Energy (kcal) 2892±1380 2445±1557 0.400
Protein (g) 84.42±36.21 58.53±28.25 0.031Carbohydrate (g) 440±241 291±117 0.031Fiber (g) 33.85±21.91 37.20±25.00 0.692Fat (g) 92.12±49.37 114.27±136.70 0.557Vitamin C (mg) 159±120 120±111 0.349Iron (mg) 30.64±15.18 20.06±18.63 0.091Sodium (mg) 4082±2226 9144±10840 0.086Calcium (mg) 1219±388 889±503 0.048Vitamin B12 (mcg) 4.96±3.91 1.72±1.17 0.003Vitamin A (RE) 399±273 142±113 0.001Manganese (mg) 4.58±3.51 11.25±6.26 0.001
Table 2 Physical activity, BMI and nutrient intake of Asian Indians living in San Diego and Coimbatore: Mean±SD
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RESULTS & DISCUSSION CONT’D
Variables In San Diego>10 years (N=8)
In San Diego≤ 10 years (N=7) p- value
BMI 25.51 ±2.60 24.48±2.01 0.412METs minutes/week 2778±2151 2137±2208 0.579Energy (Kcal) 2800±1267 2997±1596 0.794Carbohydrate(g) 414±227 470±271 0.670Protein (g) 82.88±39.52 86.18±35.08 0.867Fiber (g) 34.60±24.36 32.99±20.65 0.894Fat (g) 88.63±56.72 96.11±43.59 0.782Vitamin C (mg) 202±134 109±83 0.140Iron (mg) 33.06±16.49 27.86±14.25 0.528Sodium (mg) 4611±2101 3477±2368 0.343Calcium (mg) 1205±286 1235±506 0.888Vitamin B12 (mcg) 5.16±3.09 4.73±4.94 0.839Vitamin A (RE) 478±323 309±184 0.246Manganese (mg) 4.36±3.68 4.83±3.56 0.804
Table 3 Physical activity, BMI and nutrient intake of Asian Indians based on years of living in San Diego (Mean±SD)
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CONCLUSION
Place of living impacted intake of certain macro and micronutrient of Asian Indians.
carbohydrate (P= 0.031) protein (P=0.031) calcium (P=0.048) vitamin A (P=0.001) vitamin B12 (P=0.003) manganese (P=0.001)
But no significant difference on PA, BMI, energy intake and certain nutrient intake between SD and Coimbatore was detected
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Strength of the study Pioneer study Validated measures used
Limitations of the study A single 24-hr dietary recall Nutrient analysis software (standardization) Non-random convenience sample Type of study sample Self reported information
Future study warranted Large sample size 24-hr diet recall → 2 days and 1 weekend Blood samples – risk factors for chronic diseases
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