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Multi-centre Household Chronic Disease Risk Factor (CDRF) Study
Preet Dhillon, Dilip JhaDewan Alam, Amit Dias, Joseph Williams
Shah Ebrahim
Project period: Jan. 2011-Jan. 2013
Funded by the Wellcome Trust, UK
Objectives
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Prevalence of household & individual non-communicable disease (NCD) risk factors and outcomes in rural populations
Feasibility of community-based interviews, point-of-care diagnostics and electronic data capture
Evaluate clustering of NCD’s in households, effects of NCD’s on expenditures, HH members & health care decision-making
Methods
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◊ Design: Cross-sectional, community-based
◊ Sample size:250 households x 3 partner sites 3000 total
◊ Study population: AdultsChildren 2+ years
◊ Locations: Matlab, BangladeshCarambolim, GoaSirudhavur, Chennai
Data collection
◊ Household-level data- Cooking fuel exposure- Salt, sugar, oil- Household expenditures, insurance
◊ Individual-level data
Questionnaires:- Tobacco, alcohol, physical activity, diet, medicine- Disabilities, pain, falls, urinary- Mental health, neighbourhood, networks
Physical Measurements:- Anthropometrics, body fat- Lung function, visual acuity, grip strength- Blood pressure, fasting glucose, 24-hr urine
Matlab (n=1143) Carambolim (n=1212) Sirudhavur (n=940)
Men Women Men Women Men Women
Age, yrs (SD)
30.5 (22.0)
30.0 (19.2)
29.0 (18.4)
33.6(19.0)
28.2 (17.1)
30.5 (18.1)
EducationIlliterate 48 47 17 34 20 35Primary school 23 18 38 35 18 18Secondary school 30 35 34 28 15 41
OccupationAt home, unemployed, student
46.4 96.9 50.4 71.5 41.4 61.0
Unskilled manual, farming
16.7 1.2 28.2 21 39.3 32.8
Skilled manual 16.7 0.3 8.5 1.3 6.3 2.3
Semi-/Professional 19.6 1.4 12.2 5.6 6.7 2.3
Cigarettes/Beedi 46 0 15 6 33 0.3Tobacco 13 31 14 11 28 28Alcohol n/a n/a 30 0.2 75 1.4
Results
Matlab (n=1143) Carambolim (n=1212) Sirudhavur (n=940)
Men Women Men Women Men Women
Age, yrs (SD)
30.5 (22.0)
30.0 (19.2)
29.0 (18.4)
33.6(19.0)
28.2 (17.1)
30.5 (18.1)
EducationIlliterate 48 47 17 34 20 35Primary school 23 18 38 35 18 18Secondary school 30 35 34 28 15 41
OccupationAt home, unemployed, student
46.4 96.9 50.4 71.5 41.4 61.0
Unskilled manual, farming
16.7 1.2 28.2 21 39.3 32.8
Skilled manual 16.7 0.3 8.5 1.3 6.3 2.3
Semi-/Professional 19.6 1.4 12.2 5.6 6.7 2.3
Cigarettes/Beedi 46 0 15 6 33 0.3Tobacco 13 31 14 11 28 28Alcohol n/a n/a 30 0.2 75 1.4
Results
Matlab (n=1143) Carambolim (n=1212) Sirudhavur (n=940)
Men Women Men Women Men Women
High fasting glucose(Glucose > 126 mg/dl) - - 10.0 8.0 7.0 4.9
Hypertension(SBP>140 or DBP>90 mmHg or BP meds)
9.5 10.4 23.6 18.3 15.2 8.8
Body Mass Index23+ kg/m2 21 33 27 40 27 3225+ kg/m2 10 18 15 25 16 21
DepressionAny (PHQ>5) 11 20 9 22 37 61
Disability(WHO-DAS II> 5) 9 29 6 19 35 64
Airflow obstruction(Obs. Vs.pred < 0.7) 6.4 2.7 5.1 3.7 10.1 12.3
Results
Exposure to biomass fuel◊ Household-level questionnaire
2.1 Does the house have electricity? 1=No, 2=Yes
2.2 Fuel for cooking
1=Kerosene 5=Wood 9=Animal Dung/cake 2=Charcoal 6=Agriculture/crop 10=Shrub/Grass 3=Coal 7=Gobar Gas/bio gas 11=Other 4=Gas 8=Electricity 12=None
Primary Fuel
Secondary Fuel
2.3 Where is the cooking for the household done?
1=Inside the house 2=Inside the house in a separate kitchen 3=Outside the house 4=Both inside and outside
2.4 Does the inside cooking area have the following? 1=No 2=Yes, 3=Not Applicable
Window Chimney Exhaust
2.5 On average, how many months per year do you cook inside? (0-12 months, 99=unknown)
Primary Fuel
Secondary Fuel
2.6 On average, how many months per year do you cook outside?
(0-12 months, 99=unknown)
Primary Fuel
Secondary Fuel
Lung function data
◊ Spirometry –5 blows (FEV1, FVC, Predicted)
◊ Exclusion criteria:- Surgeries in past 3 months (eg, eye, heart)- Heart attack in past 3 mos, suffers from heart ailment- Pulse > 120 beats/min- Blood pressure greater than 180 (SBP)/ 100 (DBP)- Epilepsy, Pregnant, breast feeding
◊ Re-schedule if:- Respiratory infection, bronchodilators, smoking
◊ Comments – position, unable to complete, unable to understand, refused to cooperate, etc.
Spirometry
“A method for assessing lung function by measuring the volume of air a patient can expel from the lungs after a maximal inspiration”
It is then compared with predicted normal values based on age, height, ethnicity, gender to gauge airway obstruction
◊ Uses of Spirometry:- Gold standard (other clinical-based measures)- Variations in technical abilities, interpretations- Used to distinguish asthma vs. COPD- Management of respiratory disease- Epilepsy, Pregnant, breast feeding
Airway obstruction◊ Spirometry data:
– FVC : Forced Vital Capacity – total volume of air patient can forcibly exhale in one breath (litres)
- FEV1: Forced Expiratory Volume in 1 second- volume of air patient can exhale in the 1st second of exhalation (litres)
- FEV1/FVC: Ratio expressed as a fraction
◊ Interpreting the data:- Normal FEV1/FVC: 0.7-0.8- Airway obstruction < 0.7 (COPD post-bronchodilator)- Caution with 70+ years (overdx; 0.65 threshold OK)- Flow-volume measurement: traces flow rate against
rate of air exhaled to produce a flow-volume curve
Spirometry curve
* GOLD: 3 blows that are consistent and within 5% of each other is ideal•Normal: Volume-time curve rises rapidly & smoothly & plateaus within 3-4 seconds
Flow-vol curves
Concluding points
◊ Comparison with national/other data- Similarities: tobacco use, hypertension, depression- Differences: alcohol abuse- First time: physical activity, disability
◊ Gender differences- Health awareness- Tobacco & alcohol use- Depression
◊ Potential –Intra-/inter-household NCD pathways & effects
◊ Challenges – Recruitment to clinics, male migrants, blood donation, spirometry in women
Thank you
Wellcome Trust, UK
International Centre for Diarrheal Disease Research, Bangladesh (ICDDR,B)Sangath, Goa
Voluntary Health Services (VHS), ChennaiHealthChakra, HandsRel
Ms. Bavani PriyaDr. Rohit AjgaonkarMs. Sherin Abraham
Dr. Shariful IslamDedicated field staff
Study participants in Matlab, Carambolim & Sirudhavur
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