Srinivasan Kannan

Incidence of hypertension and its risk factors in rural Kerala, India: A community-based cohort study

OBJECTIVES To investigate the incidence of hypertension and its risk factors in Kerala, India where the epidemiological transition is more advanced than elsewhere in India. STUDY DESIGN Prospective cohort study. METHODS A sample of 297 individuals (aged 15-64 years) in rural Kerala, India, who were free of hypertension at study enrolment, were followed-up from 2003 to 2010. At enrolment, demographic characteristics and behavioural risk factors were determined by interview, and the participants underwent physical (blood pressure, height, weight and waist circumference) and biochemical examinations (fasting plasma glucose and serum lipids). At follow-up, blood pressure readings were repeated using the original tool following the same protocol. RESULTS Nearly one-quarter (23.6%) of the sample developed hypertension over a mean follow-up period of 7.1 (standard deviation 0.2) years. Age ≥35 years [relative risk (RR) 4.00, 95% confidence interval (CI) 2.37-6.03], current smoking [RR 1.99, 95% CI 1.14-2.97, population-attributable risk percent (PAR%) 13.3%], high-normal blood pressure (RR 3.53 vs optimal blood pressure, 95% CI 2.17-5.28, PAR% 44.0%) and central obesity (RR 2.45, 95% CI 1.45-3.70, PAR% 40.4%) were significantly associated with incident hypertension. Collectively, current smoking, high-normal blood pressure and central obesity accounted for 70.1% of all new cases of hypertension. Awareness, treatment and control rates of incident hypertension were 42.9%, 22.9% and 11.4%, respectively. CONCLUSIONS This rural sample showed a high incidence of hypertension. This underscores the need for primary prevention of hypertension through lifestyle modification strategies targeting individuals with high-normal blood pressure, central obesity and current smoking. The healthcare system needs to improve the level of awareness, treatment and control of hypertension in this population.

Utilization of Comprehensive Health Insurance Scheme, Kerala A Comparative Study of Insured and Uninsured Below-Poverty-Line Households

We aimed to compare the sociodemographics, health care utilization pattern, and out-of-pocket (OOP) expenses of 149 insured and 147 uninsured below-poverty-line households insured under the Comprehensive Health Insurance Scheme, Kerala, through a comparative cross-sectional study. Family size more than 4 (odds ratio [OR] = 2.34; 95% confidence interval [CI] = 1.13-4.82), family member with chronic disease (OR = 2.05; 95% CI = 1.18-3.57), high socioeconomic status (OR = 2.95; 95% CI = 1.74-5.03), and an employed household head (OR = 2.69; 95% CI = 1.44-5.02) were significantly associated with insured households. Insured households had higher inpatient service utilization (OR = 1.57; 95% CI = 1.05-2.34). Only 40% of inpatient service utilization among the insured was covered by insurance. The mean OOP expenses for inpatient services among insured (INR 448.95) was higher than among uninsured households (INR 159.93); P = .003. These findings show that urgent attention of the government is required to redesign and closely monitor the scheme.

Incidence of Tobacco Use Among Adults (15-64 Years) in Rural Kerala

We analyzed data from a cohort study in rural Kerala, India, to study the incidence of current smoking and current smokeless tobacco use. At baseline, of 452 individuals aged 15 to 64 years, 385 were current nonsmokers and 402 were current nonusers of smokeless tobacco. Over a mean follow-up of 7.1 ± 0.2 years, 5.5% became current smokers and 9.0% became current smokeless tobacco users. Among men, 21.1% (95% confidence interval [CI] = 11.1-36.4) of younger individuals (15-24 years) became current smokers and 22.2% (CI = 10.6-40.8) of older individuals (55-64 years) became current smokeless tobacco users. No women smoked both at baseline and at follow-up, but 9.7% (CI = 3.4-24.9) of older women (55-64 years) became current smokeless tobacco users. These findings call for effective implementation of India’s Cigarettes and Other Tobacco Products Act, 2003.

Achutha Menon Centre Diabetes Risk Score: A Type 2 Diabetes Screening Tool for Primary Health Care Providers in Rural India

The authors aimed to develop a diabetes risk score for primary care providers in rural India. They used the baseline data of 451 participants (15-64 years) of a cohort study in a rural area of Kerala, India. The new risk score with age, family history of diabetes, and waist circumference identified 40.8% for confirmatory testing, had a sensitivity of 81.0%, specificity of 68.4%, positive predictive value of 37.0%, and negative predictive value of 94.0% for an optimal cutoff ≥4 with an area under the receiver operating characteristic curve of 0.812 (95% confidence interval = 0.765-0.860). The new risk score with 3 simple, easy-to-measure, less time-consuming, and less expensive variables could be suitable for use in primary care settings of rural India.

Screening performance of diabetes risk scores among Asians and whites in rural Kerala, India.

We compared the screening performance of risk scores for Asians and whites for diabetes, dysglycemia, and metabolic syndrome. Our subjects were 451 people aged 15 to 64 years who participated in a cohort study from May 2003 through September 2010 in a rural area of the Thiruvananthapuram district of Kerala, India. All outcome measures showed overlap in the range of area under the receiver operating characteristic curves of Asian and white diabetes risk scores (DRSs). Asian and white DRSs performed similarly in rural India.

Seven-year longitudinal change in risk factors for non-communicable diseases in rural Kerala, India: The WHO STEPS approach

Nearly three-quarters of global deaths from non-communicable diseases (NCDs) occur in low- and middle-income countries such as India. However, there are few data available on longitudinal change in risk factors for NCDs in India. We conducted a cohort study among 495 individuals (aged 15 to 64 years at baseline) in rural Kerala state, India, from 2003 to 2010. For the present analysis, data from 410 adults (aged 20 to 64 years at baseline) who participated at both baseline and follow-up studies were analyzed. We used the World Health Organization STEPwise approach to risk factor surveillance for data collection. Age-adjusted change in risk factors for NCDs was assessed using the mixed-effects linear regression for continuous variables and the generalized estimating equation for categorical variables. The mean age of participants at baseline was 41.6 years, and 53.9% were women. The mean follow-up period was 7.1 years. There were significant increases in weight (mean change +5.0 kg, 95% confidence interval [CI] 4.2 to 5.8), body mass index (mean change +1.8 kg/m2, 95% CI 1.5 to 2.1), waist circumference (mean change +3.9 cm, 95% CI 3.0 to 4.8), waist-to-height ratio (mean change +0.022, 95% CI 0.016 to 0.027), current smokeless tobacco use (men: odds ratio [OR] 1.6, 95% CI 1.1 to 2.2), alcohol use (men: OR 2.6, 95% CI 1.9 to 3.5; women: OR 4.8, 95% CI 1.8 to 12.6), physical inactivity (OR 2.0, 95% CI 1.3 to 3.0), obesity (OR 2.2, 95% CI 1.7 to 2.8), and central obesity (OR 1.9, 95% CI 1.5 to 2.3). Over a seven-year period, several NCD risk factors have increased in the study cohort. This calls for implementation of lifestyle intervention programs in rural Kerala.

Operational research of workload using time and motion of health workers in Kerala

Public health employs women workforce in larger numbers. The success of health depends on those workers. There is a different aspect of job allocation in delivering services. Studies show health workers specifically nurses are burdened with workload. The present paper is a study on time and motion of two activities health workers. Methodology: Time and motion of two of the daily activities of the public health nurses to understand the workload. Findings: The mean of the time spent on walking from the sub-centre to the field was about 13 minutes while, mean time spent on walking within a field area was about 4 minutes. The overall mean time spent on service delivery was little above 2 minutes. In case of immunization, the mean time spent on registration was less than a minute, while the time spent for immunization was about a minute. However, they had to wait for longer duration for the beneficiaries to arrive. Conclusion: For an efficient service delivery there should be a good connectivity for the nurses to reach the field in lesser duration. For better immunization services, the system needs to focus on health promotion to attract the beneficiaries.