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High prevalence of tobacco use, alcohol use and overweight in a rural population in Tamil Nadu, India P Kaur, SR Rao, E Radhakrishnan, R Ramachandran, R Venkatachalam, MD GupteNational Institute of Epidemiology (Indian Council of Medical Research), Ayapakkam, Chennai - 600 077, India
Correspondence Address: Source of Support: None, Conflict of Interest: None DOI: 10.4103/0022-3859.74284
Background: Cardiovascular diseases are one of the leading causes of death in India. There is high prevalence of cardiovascular risk factors in urban Tamil Nadu. There are limited data on the prevalence of behavioral risk factors and overweight in rural Tamil Nadu. Aim: We estimated prevalence of behavioral risk factors, overweight and central obesity in a rural population in Tamil Nadu, India. Setting and Design: We conducted a cross-sectional survey in 11 villages in Kancheepuram/Thiruvallur districts, Tamil Nadu. Materials and Methods: Study population included 10,500 subjects aged 25-64 years. We collected data on behavioral risk factors and anthropometric measurements. Body mass index (BMI) was categorized using the classification recommended for Asians. Central obesity was defined as waist circumference ≥90 cm for men and ≥80 cm for women. We computed proportions for all risk factors and used trend chi-square to examine trend. Results: Among the 10,500 subjects, 4927 (47%) were males. Among males, 1852 (37.6%) were current smokers and 3073 (62.4%) were current alcohol users. Among females, 840 (15.1%) were smokeless tobacco users. BMI was ≥23.0 kg/m 2 for 1618 (32.8%) males and 2126 (38.2%) females. 867 (17.6%) males and 1323 (23.7%) females were centrally obese. Most commonly used edible oil was palm oil followed by sunflower oil and groundnut oil. Conclusion: We observed high prevalence of tobacco use, alcohol use and central obesity in the rural population in Tamil Nadu. There is need for health promotion programs to encourage adoption of healthy lifestyle and policy interventions to create enabling environment. Keywords: Alcohol, India, overweight, rural population, smoking
India is a developing country going through health transition characterized by a rising burden of chronic diseases. Cardiovascular diseases accounted for 29% of the deaths and 11% of disability-adjusted life years (DALY) lost in 2005. [1] In India, 70% of the population lives in rural areas and significant rural urban differences in the prevalence of cardiovascular disease and related risk factors have been described. [2] Coronary artery disease (CAD) prevalence is reported to be 8-10% in urban and 3-4% in rural India. [1] Prevalence of tobacco was higher among rural as compared to urban population, both among males (61% vs. 50%, respectively) and females (13% vs. 11%, respectively) in a recent national survey. [3] Recent studies from select rural populations indicated high prevalence of smoking, overweight and hypertension. [4],[5] Tamil Nadu is one of the southern states in India with a population of 62 million and 44% population living in urban areas. [6] It ranks among the five states with highest human development index and had rapid rise in the GDP in past decade. [7] Socioeconomic development and urbanization has set off the epidemiological transition in the state. This is evident from the recent survey on mortality pattern in Tamil Nadu, which showed that 25% of the deaths were due to circulatory system diseases. [8] In addition, recent studies from Chennai, a large metropolitan city in Tamil Nadu, showed high prevalence of behavioral risk factors and obesity. [9],[10] In contrast to urban areas, there are relatively few data on the prevalence of risk factors among rural population in various age-groups from Tamil Nadu. We conducted a survey to estimate prevalence of tobacco use, alcohol use, overweight and obesity in a rural population in Tamil Nadu. We also determined risk factors associated with tobacco use, alcohol use and obesity in a rural population in Tamil Nadu.
Study design, setting and participants We conducted a cross-sectional survey in rural population from 11 villages in the districts of Kancheepuram and Thiruvallur in Tamil Nadu. These villages are approximately 50-70 km west of Chennai, fourth largest metropolitan city in India. In the study villages, all adults aged 25-64 years were considered eligible for the study. We obtained free and informed consent for the questionnaire-based interview and physical measurements. We obtained approval from our Institutional Ethics Committee. Sample size This was a baseline survey to establish surveillance for cardiovascular risk factors in the field practice area of our institution. Therefore, we used World Health Organization (WHO) recommendation for surveillance of non-communicable disease risk factors. As per the recommendations, minimum sample size is 250 subjects in each 10 year age and sex group (25-34, 35-44, 45-54, 55-64 years). [11] However, we included all adults 25-64 years age-group in the selected villages ensuring minimum sample size is reached in all age and sex groups. We increased the sample size taking into account attrition of the cohort over period of time. Questionnaire for demographic and behavioral risk factors We used questionnaire to collect data on demographic and behavioral risk factors. Questionnaire included socio-demographic data (age, gender, education, occupation, and income), personal medical history of cardiovascular disease, diabetes, hypertension and family history of cardiovascular disease, diabetes, and hypertension. Tobacco and alcohol questionnaire included data on self-reported duration and frequency of tobacco and alcohol consumption. We collected data on the type of oil used for cooking purpose. Anthropometric measurements Weight was measured in the upright position to the nearest 0.1 kg using calibrated weighing scale. Height was measured without shoes to the nearest 0.1 cm using calibrated stadiometer. Body mass index (BMI) was calculated by dividing observed weight by height squared (kg/m 2 ). Waist circumference (WC) was measured to the nearest 0.1 cm at the narrowest point between lower end of the rib cage and iliac crest.
Smoker: Smoker was defined as a person who had smoked at least 100 cigarettes over his/her lifetime. In addition, current smoker was defined as a person who continued to smoke at the time of survey daily or occasionally, and ex-smoker was defined as a person who had quit smoking. [12] Alcohol consumption: Current consumer was defined as a person who had consumed alcohol in the past 12 months. Past consumer was defined as a person who was consuming alcohol in the past, but did not consume alcohol in past 12 months. Regular consumer was defined as a person who consumed alcohol at least once in a week. BMI classification: Subjects were classified using WHO classification and classification recommended for Asians for BMI. Categories as per WHO classification are <18.5 kg/m 2 as underweight, 18.5-24.99 kg/m 2 as normal, 25.0-29.99 kg/m 2 as overweight and ≥30.0 kg/m 2 as obese. [13] Categories as per Asian classification are <18.5 kg/m 2 as below normal, 18.5-22.99 kg/m 2 as normal, 23.0-27.4 kg/m 2 as increased risk, ≥27.5 kg/m 2 as high risk. [14] Central obesity was defined as WC ≥ 90 cm for men and WC ≥ 80 cm for women. [15] Statistical methods We computed the sex wise, age-group wise and overall proportions for all risk factors with 95% confidence intervals (CI). We used trend chi-square to examine trend of various risk factors across the four age-groups separately for males and females. All analyses were two-tailed and P value <0.05 was considered statistically significant. We conducted univariate analysis to identify risk factors associated with current smoking, alcohol use among males, smokeless tobacco use among females and central obesity among both males and females. We computed unadjusted odds ratio (OR) in the univariate analysis. We did stratified analysis to identify the confounders. We used multiple logistic regression to compute adjusted odds ratio (AOR) including confounders and interaction terms in the models. We used Epi-info version 3.5 for data analysis.
The survey was conducted in 11 villages from March 2005 to March 2007. We enumerated these villages and covered 5919 households with a total population of 25,513. Among them, 11,504 (45%) were in 25-64 years of age. Of these, data are available for 10,500 (91.2%) subjects. The reasons for non response were absence after three visits [960 (95.6%)], pregnancy [18 (1.8%)], refusal [16 (1.6%)] and physically handicapped [10 (1%)]. Socio-demographic characteristics Among the 5919 households included in the survey, 1863 (31.5%) households lived in Kutcha (house made with mud) house. Family size was less than five for 3350 (56.6%) households. 5281 (89.2%) were Hindus, 580 (9.8%) were Christians and 58 (1.0%) were Muslims. We collected data for 10,500 subjects of whom 4927 (46.9%) were males. The age distribution showed that 3758 (35.8%) subjects were of 25-34 years, 3185 (30.3%) were of 35-44 years, 2179 (20.8%) were of 45-54 years and 1378 (13.1%) were of 55-64 years. Among males, 620 (12.6%) had never attended school, 2015 (41.3%) were working as agricultural or other laborers, 1570 (32.2%) were employed in government or private sector and 561 (11.5%) were self-employed. Among females, one third had never attended school, 3072 (55.3%) were homemakers, 1447 (26%) were working as agricultural or other laborers and 645 (11.6%) were employed in government or private sector [Table 1].
Marital status of males showed that 4472 (90.8%) were married, 389 (7.9%) were unmarried and 56 (1.1%) were widowed. On the other hand, 4466 (80.1%) females were married, 978 (17.5%) were widowed and 92 (1.7%) were unmarried. Number of widowed females in age-groups of 25-34, 35-44, 45-54 and 55-64 years were 52 (2.6%), 209 (11.9%), 314 (27.8%) and 411 (52.2%), respectively. The median per capita annual income was Rs. 7500 (interquartile range: Rs. 5267-Rs. 11,100). Personal and family medical history Personal history of hypertension, diabetes, ischemic heart disease and stroke was present for 565 (5.4%), 417 (4.0%), 56 (0.5%) and 27 (0.3%) subjects, respectively. Family history of hypertension, diabetes, ischemic heart disease and stroke was present for 1246 (11.9%), 1420 (13.5%), 539 (5.1%) and 477 (4.5%) subjects, respectively [Table 2].
Behavioral risk factors Tobacco consumption, defined as ever used tobacco in the lifetime, was prevalent among 2993 (60.7%) males and 841 (15.1%) females. Among male users, type of tobacco use was smoking for 2309 (46.9%) and smokeless tobacco for 577 (11.7%) subjects. Mean (SD) age at which males started smoking was 19.9 (6.32) years. Among males, there were 457 (9.3%) ex-smokers and 1852 (37.6%) current smokers of whom 1765 (35.8%) were daily smokers. Number of daily smokers who smoked <10 cigarettes per day were 791 (44.8%), 10-19 cigarettes per day were 541 (30.7%) and 20 or above were 433 (24.5%). Smokeless tobacco use was present for 840 (15.1%) females. Only one female was an ex-smoker. Alcohol consumption, defined as ever used alcohol in the lifetime, was prevalent among 3438 (69.8%) males and 70 (1.3%) females. Current consumption in the past 12 months was prevalent among 3073 (62.4%) males and 15 (<1%) females. Among males, frequency of current alcohol consumption was at least once a week for 1437 (29.2%) and less than once a week for 1636 (33.2%). We collected data on the type of oil used for cooking. Most commonly used oil was palm oil [4178 (39.8%)] followed by sunflower oil [3680 (35.0%)], groundnut oil [3059 (29.1%)], vanaspathi [599 (5.7%)], ghee [339 (3.2%)] and gingely oil [193 (1.8%)]. There was overlap with some households using more than one type of oil. Generalized and central obesity The results of anthropometric measurements are expressed as mean (SD) among males and females. Mean BMI was 21.5 (3.75) kg/m 2 and 22.1 (4.44) kg/m 2 and WC was 79.0 (10.93) cm and 72.1 (10.62) cm, respectively, for males and females. Based on WHO classification, overweight (25.0-29.9 kg/m 2 ) and obesity (≥30 kg/m 2 ) were present for 771 (15.6%) and 92 (1.9%) males, respectively, and 1006 (18.1%) and 297 (5.3%) females, respectively. Based on the classification recommended for Asians, BMI of ≥23.0 kg/m 2 was present for 1618 (32.8%) males and 2126 (38.2%) females. Central obesity using WC cut-off was present for 867 (17.6%) males and 1323 (23.7%) females. Age-specific prevalence of risk factors Among males, prevalence of current smoking increased across the age-groups and smokeless tobacco use decreased across age-groups. The regular alcohol use increased from the age-group 25-34 to 35-44 years and declined thereafter. Prevalence of smokeless tobacco use among females increased across the age groups [Table 3].
Prevalence of increased risk BMI declined in both males and females after 44 years. However, prevalence among females was higher than males in all age groups above 35 years. Similarly, we observed higher prevalence of central obesity among females as compared to males in all groups. Central obesity reached a plateau after 44 years in females and declined in males [Table 3]. Risk factors for tobacco use, alcohol use and central obesity We identified risk factors for smokeless tobacco use among females. Increasing age, decreasing level of education, being manual worker and being widow were significantly associated with smokeless tobacco use [Table 4]. We identified the risk factors associated with current smoking among males. Increasing age, lower level of education, being manual worker and regular alcohol consumption were significantly associated with current smoking [Table 5].
Alcohol use among males was significantly associated with lower level of education, manual work and current smoking [Table 5]. Central obesity was associated with higher education among both males and females. Among females, central obesity was associated with increasing age but the same was not true among males. Among males, central obesity was associated with occupation other than being manual workers [Table 4] and [Table 5]. We also analyzed risk factors for overweight (BMI ≥ 25 kg/m 2 ) for males and females and risk factors were similar to central obesity (data not presented here).
Our study described the burden of tobacco use, alcohol use, overweight and central obesity with gender differences and age-group wise trends in a large sample of rural population in south India. Burden of cardiovascular risk factors in this population reflects epidemiological transition even in rural population in Tamil Nadu which is classified as middle to late transition state based on various health indicators. [16] Prevalence of smoking among males was high, particularly among less educated and manual workers. This was consistent with a national survey which showed that rural males had higher smoking and alcohol use as compared to rural females, urban males and females. [3] In contrast to smoking, smokeless tobacco use was observed both among males and females. Smokeless tobacco use was higher among old, widowed and manual worker females. Various studies from rural areas of India reported smokeless tobacco usage among 3-53% men and 3-49% women. High smokeless tobacco use among women is due to social acceptance and belief regarding palliative role for minor ailments like toothache. Moreover, there is low awareness regarding associated health hazards. [17] Health promotion programs at the community level and through mass media with socio-culturally appropriate messages can help raise awareness among rural population. This should be supplemented by effective implementation of policy interventions such as smoke free public places that was recently launched in India. [18] A project demonstrated feasibility and success of tobacco free villages in one of the districts in Kerala; such initiatives need to be scaled up in other states including Tamil Nadu. [19] High prevalence of alcohol use is also consistent with several community- and hospital-based surveys that reported increasing prevalence of alcohol use in the country including Tamil Nadu. [20] Similar to tobacco use, alcohol use was also higher in vulnerable groups such as manual workers and less educated males in our study population. Tamil Nadu has a unique scenario where the government is the sole distributor of alcohol with wide network of sales outlets and administered pricing. This has likely led to increase in alcohol consumption as seen with an increase in the revenue in the state in past few years. [21] Conflicting roles of government in increasing alcohol sales on one hand and protecting health on the other hand makes it challenging to address this issue from policy viewpoint. However, other interventions such as increasing awareness regarding harmful effects of alcohol, capacity building at the primary care level for treating alcohol related problems and rehabilitation may be initiated to address this issue. One of the important risk factors from the dietary perspective was use of palm oil by large proportion of the population. The reason for preference of this oil was availability through public distribution system and its low cost in the retail market. Palm oil has high proportion of saturated fat and is associated with high total and low density lipoprotein cholesterol. [22] There may be lessons to learn from public health policy intervention in Mauritius, where replacing palm oil with soyabean oil led to lower cholesterol levels in the population. [23] Prevalence of overweight and central obesity was consistent with previous studies in rural areas. [4],[5] We observed higher prevalence of overweight and obesity among females. Similar trend was observed in a recent study from northern India. [24] Prevalence of overweight and obesity in our population was higher than observations made in a nutrition survey in Tamil Nadu (BMI ≥ 23 kg/m 2 : men 22.5%, females 25.1%). [25] This could be due to proximity of our study population to urban areas and therefore changes in the lifestyle leading to overweight/obesity. We observed a decline in overweight with increasing age that was more pronounced in males as compared to females. This was in contrast to observations in urban populations where there is increase in overweight with increasing age. [10] The reasons for such trend could be high prevalence of smoking and alcohol in rural population, poor nutritional status, survival of the healthier subset, or high mortality among males above 44 years. In contrast to tobacco and alcohol use, obesity was higher among educated subset of the population. Health education programs for weight reduction need to target this group to reduce the risk of obesity related diseases. The strength of our study is that this is one of largest studies from rural population where gender- and age-specific prevalence of risk factors was studied. Our study provides baseline data that can be used for planning interventions for control of cardiovascular disease. One of the relevant issues for public health policy is consideration of the fact that this population is socioeconomically underprivileged and has lower educational levels. Therefore, they may not be able to carry out behavioral modification interventions in the absence of enabling environment. There were few limitations of study. One of the limitations was purposive sample from a rural population, 40-50 km from the city, which may not be representative of general rural population. Hence, prevalence of tobacco use, alcohol use, overweight and central obesity was high in this rural population proximal to urban area in Tamil Nadu. There is an urgent need for health promotion campaigns to raise awareness regarding risk factors such as smoking, alcohol, overweight and encourage adoption of healthy lifestyles. However, an enabling environment needs to be created by implementing relevant public policies to facilitate behavioral modification.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]
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