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      Exercise and eating habits among urban adolescents: a cross-sectional study in Kolkata, India

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          Abstract

          Background

          Unhealthy eating and lack of exercise during adolescence culminated into earlier onset and increasing burden of atherosclerotic cardiovascular diseases (CVDs) worldwide. Among urban Indian adolescents, prevalence of these risk factors of CVD seemed to be high, but data regarding their pattern and predictors was limited. To address this dearth of information, a survey was conducted among urban adolescent school-students in Kolkata, a highly populated metro city in eastern India.

          Methods

          During January–June, 2014, 1755 students of 9th-grade were recruited through cluster (schools) random sampling. Informed consents from parents and assents from adolescents were collected. Information on socio-demographics, CVD-related knowledge and perception along with eating and exercise patterns were collected with an internally validated structured questionnaire. Descriptive and regression analyses were performed in SAS-9.3.2.

          Results

          Among 1652 participants (response rate = 94.1%), about 44% had poor overall knowledge about CVD, 24% perceived themselves as overweight and 60% considered their general health as good. Only 18% perceived their future CVD-risk and 29% were engaged in regular moderate-to-vigorous exercise. While 55% skipped meals regularly, 90% frequently consumed street-foods and 54% demonstrated overall poor eating habits.

          Males were more likely to engage in moderate-to-vigorous exercise [adjusted odds ratio (AOR) = 3.40(95% confidence interval = 2.55–4.54)] while students of higher SES were less likely [AOR = 0.59(0.37–0.94)]. Males and those having good CVD-related knowledge were more likely to exercise at least 1 h/day [AOR = 7.77(4.61–13.07) and 2.90(1.46–5.78) respectively].

          Those who perceived their future CVD-risk, skipped meals more [2.04(1.28–3.25)] while Males skipped them less [AOR = 0.62(0.42–0.93)]. Subjects from middle class ate street-foods less frequently [AOR = 0.45(0.24–0.85)]. Relatively older students and those belonging to higher SES were less likely to demonstrate good eating habits [AOR = 0.70(0.56–0.89) and 0.23(0.11–0.47) respectively]. A large knowledge-practice gap was evident as students with good CVD-related knowledge were less likely to have good eating habits [AOR = 0.55(0.32–0.94)].

          Conclusions

          CVD-related knowledge as well as eating and exercise habits were quite poor among adolescent school-students of Kolkata. Additionally, there was a large knowledge-practice gap. Multi-component educational interventions targeting behavioral betterment seemed necessary for these adolescents to improve their CVD-related knowledge, along with appropriate translation of knowledge into exercise and eating practices to minimize future risk of CVDs.

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          Most cited references41

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          Risk factors for early myocardial infarction in South Asians compared with individuals in other countries.

          South Asians have high rates of acute myocardial infarction (AMI) at younger ages compared with individuals from other countries but the reasons for this are unclear. To evaluate the association of risk factors for AMI in native South Asians, especially at younger ages, compared with individuals from other countries. Standardized case-control study of 1732 cases with first AMI and 2204 controls matched by age and sex from 15 medical centers in 5 South Asian countries and 10,728 cases and 12,431 controls from other countries. Individuals were recruited to the study between February 1999 and March 2003. Association of risk factors for AMI. The mean (SD) age for first AMI was lower in South Asian countries (53.0 [11.4] years) than in other countries (58.8 [12.2] years; P or =once/wk, 10.7% vs 26.9%). However, some harmful factors were more common in native South Asians than in individuals from other countries (elevated apolipoprotein B(100) /apolipoprotein A-I ratio, 43.8% vs 31.8%; history of diabetes, 9.5% vs 7.2%). Similar relative associations were found in South Asians compared with individuals from other countries for the risk factors of current and former smoking, apolipoprotein B100/apolipoprotein A-I ratio for the top vs lowest tertile, waist-to-hip ratio for the top vs lowest tertile, history of hypertension, history of diabetes, psychosocial factors such as depression and stress at work or home, regular moderate- or high-intensity exercise, and daily intake of fruits and vegetables. Alcohol consumption was not found to be a risk factor for AMI in South Asians. The combined odds ratio for all 9 risk factors was similar in South Asians (123.3; 95% confidence interval [CI], 38.7-400.2] and in individuals from other countries (125.7; 95% CI, 88.5-178.4). The similarities in the odds ratios for the risk factors explained a high and similar degree of population attributable risk in both groups (85.8% [95% CI, 78.0%-93.7%] vs 88.2% [95% CI, 86.3%-89.9%], respectively). When stratified by age, South Asians had more risk factors at ages younger than 60 years. After adjusting for all 9 risk factors, the predictive probability of classifying an AMI case as being younger than 40 years was similar in individuals from South Asian countries and those from other countries. The earlier age of AMI in South Asians can be largely explained by higher risk factor levels at younger ages.
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            A simplified general method for cluster-sample surveys of health in developing countries.

            General guidelines are presented for the use of cluster-sample surveys for health surveys in developing countries. The emphasis is on methods which can be used by practitioners with little statistical expertise and no background in sampling. A simple self-weighting design is used, based on that used by the World Health Organization's Expanded Programme on Immunization (EPI). Topics covered include sample design, methods of random selection of areas and households, sample-size calculation and the estimation of proportions, ratios and means with standard errors appropriate to the design. Extensions are discussed, including stratification and multiple stages of selection. Particular attention is paid to allowing for the structure of the survey in estimating sample size, using the design effect and the rate of homogeneity. Guidance is given on possible values for these parameters. A spreadsheet is included for the calculation of standard errors.
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              Decline in physical activity in black girls and white girls during adolescence.

              Physical activity declines during adolescence, but the underlying reasons remain unknown. We prospectively followed 1213 black girls and 1166 white girls enrolled in the National Heart, Lung, and Blood Institute Growth and Health Study from the ages of 9 or 10 to the ages of 18 or 19 years. We used a validated questionnaire to measure leisure-time physical activity on the basis of metabolic equivalents (MET) for reported activities and their frequency in MET-times per week; a higher score indicated greater activity. The respective median activity scores for black girls and white girls were 27.3 and 30.8 MET-times per week at base line and declined to 0 and 11.0 by year 10 of the study (a 100 percent decline for black girls and a 64 percent decline for white girls, P<0.001). By the age of 16 or 17 years, 56 percent of the black girls and 31 percent of the white girls reported no habitual leisure-time activity. Lower levels of parental education were associated with greater decline in activity for white girls at both younger ages (P<0.001) and older ages (P=0.005); for black girls, this association was seen only at the older ages (P=0.04). Pregnancy was associated with decline in activity among black girls (P<0.001) but not among white girls, whereas cigarette smoking was associated with decline in activity among white girls (P<0.001). A higher body-mass index was associated with greater decline in activity among girls of both races (P< or =0.05). Substantial declines in physical activity occur during adolescence in girls and are greater in black girls than in white girls. Some determinants of this decline, such as higher body-mass index, pregnancy, and smoking, may be modifiable. Copyright 2002 Massachusetts Medical Society
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                Author and article information

                Contributors
                dr.soumitrakumar@gmail.com
                drsaumitra@yahoo.co.in
                debroy67@ymail.com
                drkajalganguly@gmail.com
                sib.dutta11@gmail.com
                +918017206285 , drtanmaymahapatra@yahoo.com
                raysanchita@yahoo.co.in
                kinni.gupta@gmail.com
                kaushik_chakrabarty@yahoo.com
                drmkdas2001@yahoo.co.in
                guhas55@gmail.com
                dr_pkdeb@rediffmail.com
                dramalcsi2009@gmail.com
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                18 May 2017
                18 May 2017
                2017
                : 17
                : 468
                Affiliations
                [1 ]GRID grid.416884.7, Department of Cardiology, , Vivekananda Institute of Medical Sciences, ; Kolkata, West Bengal 700026 India
                [2 ]Department of Cardiology, Rabindranath Tagore International Institute of Cardiac Sciences, Kolkata, West Bengal 700099 India
                [3 ]GRID grid.416241.4, Department of Cardiology, , Nilratan Sircar Medical College and Hospital, ; Kolkata, West Bengal 700014 India
                [4 ]ISNI 0000 0004 0507 4308, GRID grid.414764.4, Department of Cardiology, , Institute of Post-Graduate Medical Education and Research, ; Kolkata, West Bengal 700020 India
                [5 ]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, , Fielding School of Public Health, University of California - Los Angeles, ; Los Angeles, CA 90095 USA
                [6 ]Mission Arogya Health and Information Technology Research Foundation, Kolkata, West Bengal 700010 India
                [7 ]Medica Institute of Cardiac Sciences, Medica Super Specialty Hospital, Kolkata, West Bengal 700099 India
                [8 ]Barrackpore Population Health Research Foundation, Kolkata, West Bengal 700123 India
                [9 ]The BM Birla Heart Research Centre, Kolkata, West Bengal 700027 India
                [10 ]ISNI 0000 0004 1768 2335, GRID grid.413204.0, , Medical College and Hospital, ; Kolkata, West Bengal 700073 India
                [11 ]Charnock Hospitals Private Limited, Kolkata, West Bengal 700157 India
                [12 ]Fortis Hospitals Private Limited, Kolkata, West Bengal 700127 India
                [13 ]Mission Arogya Health and Information Technology Research Foundation, 8 Dr. Ashutosh Sastri Road, Kolkata, West Bengal 700010 India
                Article
                4390
                10.1186/s12889-017-4390-9
                5437535
                28521735
                3fdd6b9c-6270-450d-a42d-7dd765a362e6
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 31 May 2016
                : 8 May 2017
                Funding
                Funded by: Cardiological Society of India (http://www.csi.org.in/), West Bengal Branch
                Award ID: CSWB/CRRIS/13/339; 24.09.2013
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Public health
                eating habits,exercise,adolescent,urban,kolkata
                Public health
                eating habits, exercise, adolescent, urban, kolkata

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