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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