Exposure to mosquito coil and biomass fuel smoke and respiratory health in rural Tamil Nadu, India.

BACKGROUND: Mosquito coil smoke, along with biomass fuel smoke, are sources of indoor air pollution. Biomass fuel smoke has been studied as a risk factor for poor respiratory outcomes. However, in an Indian context, few studies examine the effect of mosquito coil exposure on poor respiratory outcomes at the community level. OBJECTIVES: To estimate the prevalence of the biomass fuel and mosquito coil use and to determine the association between the use of bio-mass fuel and mosquito coil and poor respiratory health. METHODS: A cross-sectional survey of 4662 individuals (above the age of 30 years) was conducted using a pre-tested questionnaire. Trained interviewers collected data on current and past use of biomass fuels and mosquito coils, usage practices and respiratory health. We computed proportions for exposure variables namely biomass fuel, mosquito coil use and other covariates. We conducted univariate analysis, followed by multivariate logistic regression. RESULTS: The prevalence of ever use of biomass fuels was high (wood: 97.9%; cow dung cake: 76.0% and crop residue: 54.4%). Current use of wood, cow dung cake and crop residue was prevalent among 75.7, 24.3 and 30.9% respondents, respectively. Almost 70% of respondents had ever used mosquito coils, whereas 54% were current users. Overall, 5.5% respondents had poor respiratory health either due to chronic bronchitis or asthma. In multivariate analysis, use of combination of all three biomass fuel types (adjusted odds ratio [AOR] 1.69, 95% confidence interval [CI]: 1.13-2.54) and use of mosquito coil more than or equal to 5 days per week (AOR 1.43, 95% CI: 1.04-1.99) were associated with poor respiratory health after adjusting for covariates age, gender, smoking, kitchen type and for each other. CONCLUSIONS: Use of biomass fuels and mosquito coils was high in the study population and was associated with poor respiratory health. Therefore, mosquito coil smoke should also be considered an important source of indoor air pollution, similar to biomass fuel exposure. Community education about these sources of indoor air pollution and increased coverage of cleaner fuels and alternative mosquito control methods should be the way forward in the rural areas.

Assessment of Carotid Arterial Stiffness in Community Settings With ARTSENS®.

OBJECTIVE: We investigate the field feasibility of carotid stiffness measurement using ARTSENS® Touch and report the first community-level data from India. METHOD: In an analytical cross-sectional survey among 1074 adults, we measured specific stiffness index ([Formula: see text]), pressure-strain elastic modulus ([Formula: see text]), arterial compliance (AC), and one-point pulse wave velocity (PWV[Formula: see text]) from the left common carotid artery. Data for established risk factors (waist circumference, blood pressure, plasma glucose, triglycerides, and HDL-C) were also collected. The association of carotid stiffness with age, gender, hypertension/diabetes, smoking, and clustering of risk factors was studied. RESULTS: Measurements were repeatable with a relative difference (RD) between consecutive readings of < 5% for blood pressure and < 15% for [Formula: see text]% of arterial diameter values. The average RDs for [Formula: see text], [Formula: see text], AC, and PWV[Formula: see text], were 20.51%, 22.31%, 25.10%, and 14.13%, respectively. Typical range for stiffness indices among females and males were [Formula: see text]: 8.12 ± 3.59 vs 6.51 ± 2.78, [Formula: see text]: 113.24 ± 56.12 kPa vs 92.33 ± 40.65 kPa, PWV[Formula: see text]: 6.32 ± 1.38 ms-1 vs 5.81 ± 1.16 ms-1, and AC: 0.54 ± 0.36 mm2 kPa-1 vs 0.72 ± 0.38 mm2 kPa-1. Mean [Formula: see text], [Formula: see text], and PWV[Formula: see text] increased (and mean AC decreased) across decades of age; the trend persisted even after excluding hypertensives and subjects with diabetes. The odds ratio of presence of multiple risk factors for [Formula: see text] kPa and/or PWV[Formula: see text] ms-1 was ≥ 2.12 or above in males. In females, it was just above 2.00 for [Formula: see text] kPa and/or PWV[Formula: see text] ms-1 and increased to ≥ 3.33 for [Formula: see text] kPa and ≥ 3.25 for PWV[Formula: see text] ms-1. CONCLUSION: The study demonstrated the feasibility of carotid stiffness measurement in a community setting. A positive association between the risk factors and carotid artery stiffness provides evidence for the device's use in resource-constrained settings. Clinical Impact: The device paves the way for epidemiological and clinical studies that are essential for establishing population-level nomograms for wide-spread use of carotid stiffness in clinical practice and field screening of 'at-risk' subjects.

Prevalence of risk factors for non-communicable diseases in a rural tribal population of Mokokchung, Nagaland, India.

Background: Non-communicable diseases (NCDs) are the leading cause of mortality in India. The northeastern part of India has a high burden of NCDs. However, data on the prevalence of risk factors for NCDs in the rural tribal population of Nagaland are limited. We estimated the prevalence and awareness level of risk factors for NCDs in the rural population of Mokokchung district, Nagaland. Methods: In a cross-sectional survey, we selected 472 subjects aged 25-64 years, stratified by age and sex, in 20 villages, using a cluster sampling technique. The WHO STEPS tools were used to collect data on behavioural risk factors, and anthropometric, blood pressure and capillary glucose measurements. The proportion of subjects with each NCD risk factor was determined overall and in various age and sex subgroups. Results: The 472 subjects had a median age of 44.5 years, 92 (19.5%) reported current smoking and 75 (15.9%) reported current alcohol use. Among 236 males, 90 (38.1 %) were current smokers and 65 (27.5%) were current alcohol users, whereas of the 236 females, only 2 (0.8%) and 10 (4.2%) were current smokers and current alcohol users, respectively. The use of smokeless tobacco was common among both males (139/236; 58.9%) and females (117/ 236; 49.6%). Inadequate intake of fruits and vegetables was reported by 189 (80.1%) males and 221 (93.6%) females. Insufficient physical activity was observed only among 16 (3.4%) participants. Prevalence of hypertension and a body mass index of 23.0-27.49 kg/m2 was 43.2% and 32.4%, respectively. Conclusions: We observed a high prevalence of behavioural risk factors for NCDs and of hypertension in rural tribal people in Nagaland. The primary healthcare system needs to be strengthened in this area to improve detection and management of hypertension. Mass and print media campaigns and provision of cessation services may also be helpful.

Hypertension treatment and control in a rural cohort in Thiruvallur, Tamil Nadu, India.

Hypertension is a public health problem with low detection and treatment rates in India. We resurveyed 1284 patients with hypertension already identified in baseline survey of the cohort in Thiruvallur district, Tamil Nadu, India. The objective was to estimate the proportion of patients with drug treatment, hypertension control and lifestyle modification at follow-up (median follow-up 27 months). Overall, only 19.9% of the patients took drugs and 45.3% had blood pressure under control. Among 256 patients on drugs, 179 (69.9%) were on a single drug, 71 (27.7%) on two drugs, and six (2.3%) on three drugs. Commonly prescribed drugs based on the prescription review were beta blockers (50.4%), calcium channel blockers (36.7%), angiotensin-converting-enzyme inhibitor (18.4%), and diuretics (11.7%). Salt reduction was reported by 49.7% of the patients. There is a need for strengthening the health systems for effective management of hypertension and patient education to ensure active involvement in the long-term care.

Diabetic retinopathy and its risk factors in patients with type 2 diabetes attending rural primary healthcare facilities in Tamil Nadu.

BACKGROUND: India has a high burden of diabetic retinopathy ranging from 12.2% to 20.4% among patients with type 2 diabetes mellitus (T2DM). A T2DM management programme was initiated in the public sector in Tamil Nadu. We estimated the prevalence of diabetic retinopathy and its associated risk factors. METHODS: We did a cross-sectional survey among patients with T2DM attending two primary health centres for treatment and follow-up in Kancheepuram, Tamil Nadu in January- March 2013. We did a questionnaire-based survey, and measured blood pressure and biochemical parameters (serum creatinine, plasma glucose, etc.) of the patients. We examined their eyes by direct and indirect ophthalmoscopy and defined diabetic retinopathy using a modified classification by Klein et al. We calculated the proportion and 95% CI for the prevalence and adjusted odds ratio (AOR) for risk factors associated with diabetic retinopathy. RESULTS: Among the 270 patients, the mean (SD) age was 54.5 (10) years. The median duration of T2DM was 48 months. The prevalence of diabetic retinopathy was 29.6%. Overall, 65.9% of patients had hypertension, 14.4% had nephropathy (eGFR <60 mg/dl) and 67.4% had neuropathy. Among patients with comorbid conditions, 60%, 48%, 32%, and 3% were already diagnosed to have hypertension, neuropathy, retinopathy, and nephropathy, respectively. The risk factors for diabetic retinopathy were hypertension (AOR 3.2, 95% CI 1.7-6.3), duration of T2DM >5 years (AOR 6.5, 95% CI 3.6-11.7), poor glycaemic control (AOR 2.4, 95% CI 1.4-4.4), and nephropathy (AOR 2.3, 95% CI 1.1-4.6). CONCLUSIONS: There was a high burden of undetected retinopathy and other comorbid conditions among patients with T2DM. Early detection of comorbid conditions and glycaemic control can be improved by training care-providers and educating patients.

Prevalence, awareness, treatment, control and risk factors for hypertension in a rural population in South India.

OBJECTIVES: Hypertension is a major public health problem with prevalence ranging 22-30% in urban India. There are few data on hypertension epidemiology in rural India. We conducted a survey to estimate prevalence, awareness, treatment, control and risk factors for hypertension in a rural population in south India. METHODS: We did cross-sectional survey in 11 villages in Tamil Nadu. We collected data on behavioral risk factors, anthropometric and blood pressure measurements. We defined hypertension according to WHO criteria. RESULTS: Study population included 10,463 subjects aged 25-64 years. Among them, 4,900 (46.8%) were males. Hypertension was present for 2,247 (21.4%) subjects and 1,682 (74.9%) among hypertensives were newly detected. Overall 20% were on treatment and 6.6% had blood pressure control. Age ≥35 years, BMI ≥ 23 kg/m(2) and central obesity were risk factors significantly associated with hypertension (p < 0.05). In addition, alcohol consumption, higher education level were risk factor among males and family history of hypertension was risk factor among females (p < 0.05). CONCLUSION: Hypertension is an emerging challenge in rural India. We need health promotion programs and reorientation of primary health care to improve hypertension detection and management.

The metabolic syndrome and associated risk factors in an urban industrial male population in South India.

BACKGROUND: The metabolic syndrome is characterized by clustering of risk factors, which predisposes subjects to increased risk of diabetes and cardiovascular disease. Objectives of this study were to estimate prevalence of the metabolic syndrome and determine the association of risk factors with the metabolic syndrome in an urban industrial male population in Chennai, India. METHODS: We conducted a cross-sectional survey for male employees working in an industrial unit. The survey included questionnaire for risk factors, anthropometric and blood pressure measurements. Blood samples were collected for the fasting plasma glucose, serum cholesterol, high-density lipoprotein cholesterol and triglycerides. The metabolic syndrome was defined using International Diabetes Federation (IDF) and American Heart Association (AHA)/National Heart Lung and Blood Institute (NHLBI) criteria. RESULTS: The total numbers of male subjects included in the study were 1077. The prevalence of the metabolic syndrome was 41.3% and 51.4% using IDF and AHA/NHLBI criteria respectively. Risk factors were age above 35 years, family history of diabetes and body mass index (BMI) above 23.9 kg/m2. The consumption of more than three servings of fruits and vegetables was protective. CONCLUSION: The prevalence of the metabolic syndrome was very high in select industrial population in south India. Higher BMI and low intake of fruits and vegetables are modifiable by life style modification. Work site screening for the metabolic syndrome would facilitate the early detection and treatment.

A comparison of anthropometric indices for predicting hypertension and type 2 diabetes in a male industrial population of Chennai, South India.

OBJECTIVES: To assess the association of four obesity-related indices--body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-stature ratio (WSR)--with hypertension and type 2 diabetes among a male industrial population in south India. DESIGN, SETTING, AND PARTICIPANTS: A cross sectional study of 2148 men aged 18-69 years in two purposely selected industrial units in Chennai, India, in 2003-2005. MAIN OUTCOME MEASURES: The examination included blood pressure and anthropometric measurements (height, weight, hip circumference, and WC) to calculate BMI, WHR, and WSR. Fasting blood samples were taken to assess plasma glucose. RESULTS: Prevalence of overweight was 43.4%; prevalences of central obesity using WC > or = 90.0 cm and WHR > 0.90 were 50.0% and 70%, respectively. The prevalences of hypertension and type 2 diabetes were 26.5% and 16.3%, respectively. There was a significant increase in the prevalence of type 2 diabetes and hypertension across the quintiles for the four anthropometric indices. In logistic regression analysis, BMI and WC showed a significant graded increase in the odds ratio for hypertension after adjusting for age. In case of type 2 diabetes, only WHR showed significant increase in odds ratio across quintiles after adjusting for age and BMI. CONCLUSIONS: WHR was the best predictor for type 2 diabetes in the study sample. BMI and WC were good predictors for hypertension. We recommend that WHR should be routinely used in this clinical setting in addition to BMI to detect persons at high risk in these industrial units. Prospective studies are needed to provide evidence of the predictive power of anthropometric indices for Asian Indians.

Prevalence and distribution of cardiovascular risk factors in an urban industrial population in south India: a cross-sectional study.

BACKGROUND: Cardiovascular diseases (CVD) are leading cause of death in developing countries including India. The huge burden of CVD in Indian subcontinent is the consequence of the large population and high prevalence of cardiovascular risk factors. This study was done to determine the prevalence of cardiovascular risk factors in two industrial units in Chennai, India. METHODS: Survey of behavioural risk factors using structured questionnaires and anthropometric measurements were done for the study population. Blood samples were collected for the fasting plasma glucose and serum cholesterol. Trend chi-square was employed to test the linear trend. RESULTS: The total study population included 2262 male subjects. Blood samples were collected for 2148 (95.0%) subjects. Age range was 18-69 years. Prevalence of major cardiovascular risk factors was: current smokers 462 (20.2%), body mass index > or = 23 kg/m2 1510 (66.8%), central obesity 1589 (70.2%), hypertension 615 (27.2%), diabetes mellitus 350(16.3%) and total cholesterol > or = 200mg/dl in 650(30.3%). CONCLUSIONS: The study results indicated high prevalence of behavioural risk factors, central obesity, hypertension and diabetes in a select group of middle and high-income young urban males. The long-term follow-up in such settings will provide an opportunity to understand the influence of risk factors on cardiovascular disease outcomes.