DOI 10.1515/ijamh-2013-0331 Int J Adolesc Med Health 2014; 26(4): 531–540
Karl Peltzer*, Supa Pengpid and Krishna Mohan
Prevalence of health behaviors and their associated factors among a sample of university students in India Abstract Objective: With advances in knowledge about health promotion, public health professionals are in search for the determinants of personal health behaviors. The purpose of this study was to assess the prevalence of health behaviors and its associated factors in a sample of Indian university students. Materials and methods: Using a cross-sectional survey, we assessed health behavior among a sample of randomly selected university students. The sample included 800 university students from non-health (mainly engineering and sciences) undergraduate courses of Gitam University, Visakhapatnam in India. The students were 541 (67.6%) males and 259 (32.4%) females in the age range of 17–20 years (Median age = 18.2 years, SD = 1.0). Results: On average, students engaged in 15.8 out of 25 health behavior practices. There was a high rate of overweight and obesity (26.8% and 10.7%, respectively), low rate of brushing teeth at least twice a day (28.6%), annual dental check-up (25.8%), habitual seatbelt use (23%), and poor dietary patterns (79% ate less than the recommended fruit and vegetable consumption of five servings a day, and 68.5% did not avoid eating fat and cholesterol). In multivariate analysis among men, personal constraints (Odds Ratio = OR 1.75, Confidence Interval = CI 1.09–2.82), health benefits (OR = 2.01, CI = 1.27–3.17), and not suffering from depression (OR = 0.60, CI = 0.22–0.94) were associated with the health behavior index. Among women, those who were living away from their parents or guardians (OR = 1.94, CI = 1.06–3.55), economically better off (OR = 2.16, CI = 1.00–4.63), and had higher social support (OR = 3.65, CI = 1.75–7.63), were associated with the health behavior index. Discussion: Students had a high proportion of health behavior practices. Several high health risk practices were identified, including overweight, poor dental practices, poor dietary and sleeping habits. It is hoped that the gender-specific predictors identified, including sociodemographics as well as social and mental health variables, can also be utilized in designing health promotion programs.
Keywords: health behavior; health benefits; health risk knowledge; India; university students. *Corresponding author: Professor Karl Peltzer, HIV/AIDS/SIT and TB (HAST) Research Program, Human Sciences Research Council, Private Bag X41, Pretoria 0001, South Africa, E-mail: [email protected]; Department of Psychology, University of Limpopo, Turfloop Campus, Sovenga, South Africa; and ASEAN Institute for Health Development, Madidol University, Salaya, Phutthamonthon, Nakhonpathom, Thailand Supa Pengpid: ASEAN Institute for Health Development, Madidol University, Salaya, Phutthamonthon, Nakhonpathom, Thailand; and University of Limpopo, Turfloop Campus, Turfloop, South Africa Krishna Mohan: Psychguru Mental Health Services, Palem, Madhurawada, Visakhapatnam, India; and University of Flores, Buenos Aires, Argentina
Introduction Chronic diseases, including heart disease, stroke, cancer, and diabetes are, by far, the leading causes of death worldwide, including India (1). Behavioral risk factors, including tobacco smoking, alcohol drinking, physical inactivity, sedentary behavior and obesity, are major determinants of adult chronic diseases morbidity and mortality (2–4). For instance, nearly 80% of incident cases of cardiovascular disease and Type II diabetes are attributable to physical inactivity, tobacco smoking, and unhealthy diet (1). In addition to the burden of disease attributed to single chronic behavioral risk factors, a growing body of evidence also suggests that behavioral risk factors (including physical inactivity, sedentary behavior, smoking, alcohol use, and obesity) co-occur among youth (5), and that their combinations yield greater risks for chronic diseases than the sum of their individual independent effects (6, 7). Health behaviors that are formed during childhood and adolescence can have a significant impact on the occurrence of future illnesses (8, 9). Many risk processes that lead to chronic non-communicable diseases in later life, including tobacco, alcohol, and illicit substance misuse,
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532 Peltzer et al.: Health behavior unsafe sex, obesity and lack of physical activity, typically emerge around this time (9–11). Few studies among university students in India have shown health behavior risks, such as tobacco use [7% (12), 1.7% (13), 5.3% (14), 25.1% (15), 18.3%–43.6% (16), 45% (17)], lack of physical activity [42.6% (12), 35.2% (18), 79.8% (13), 57.6% (19)], recommended at least five servings per day of fruits and vegetables [12% (12)], alcohol use [28.8% (12)], cannabis use [4.5% (20)], and overweight [17.8% –29.6% (19)]. Factors identified to be associated with health behavior include sociodemographic factors [female gender (21–26), socioeconomic status (27–29), educational achievement (30, 31), social factors [social support (32), sense of coherence (25, 33, 34), religiosity or spirituality (32, 35), sense of control (36, 37)], and health variables [risk awareness (36, 38), perceived health benefits (36, 39, 40), low depression (41), low levels of psychological distress (42, 43)]. The purpose of this study was to assess the prevalence of health behaviors and its associated factors in a sample of Indian university students.
Materials and methods Sample and procedure The sample included 800 university students from non-health (mainly engineering and sciences) courses chosen at random from the Institute of Technology and Institute of Sciences at Gitam University in India. Data were collected by a self-administered questionnaire in a classroom situation after informed consent was obtained from the participants. Permission to carry out the study was obtained from the senior faculty of the university. Ethical clearance was also obtained. The cover page of the questionnaire briefly explained the objectives of the study, provided instructions to the respondents on how to fill it up, and gave information about the researchers. It also mentioned that anonymity and confidentiality would be maintained and that the participation of students was voluntary. Finally, it specified that the collected data would be used only for research purposes.
Measures Health behavior variables Tobacco use was assessed with the question: “Do you currently use one or more of the following tobacco products (cigarettes, snuff, chewing tobacco, cigars, etc.)?” Response options were “yes” or “no” (44). Alcohol consumption was measured by asking participants as to which of the following terms best described them: non-drinker, special occasions drinker, occasional drinker, and regular drinker. Occasional and regular drinkers were asked about how many days
over the last two weeks they had had a drink, and how many drinks they had consumed on those days. These data were used to derive four categories of alcohol consumption: none, very occasional, fewer than one drink per day, and more than one drink per day over the past 14 days (36). Illicit drug use was assessed with one question, “How often have you taken drugs in the past 12 months; other than prescribed by the health care provider?” Response options were 1 = 0 times to 4 = 10 or more times. Physical activity was assessed using the International Physical Activity Questionnaire (IPAQ) short version, self-administered last 7 days (IPAQ-S7S). We used the instructions given in the IPAQ manual for reliability and validity, which was detailed elsewhere (45). To sum up the single indicators to an overall indicator of PA-related EE (Metabolic equivalent, MET min–1) is a major goal of the IPAQ instruments. In accordance with the recommendations, we followed MET estimates of IPAQ: Vigorous PA = 8 METs, moderate PA = 4 METs, and walking on average = 3.3 METs. For calculating the overall METs PA, each category was multiplied with its special MET estimate value. We also used the recommended categorical score, which referred to three levels of PA (low, moderate, and high) as proposed in the IPAQ Scoring Protocol (short form). Low activity represented individuals who did not meet the criteria for moderate and vigorous intensity categories (
Karl Peltzer*, Supa Pengpid and Krishna Mohan
Prevalence of health behaviors and their associated factors among a sample of university students in India Abstract Objective: With advances in knowledge about health promotion, public health professionals are in search for the determinants of personal health behaviors. The purpose of this study was to assess the prevalence of health behaviors and its associated factors in a sample of Indian university students. Materials and methods: Using a cross-sectional survey, we assessed health behavior among a sample of randomly selected university students. The sample included 800 university students from non-health (mainly engineering and sciences) undergraduate courses of Gitam University, Visakhapatnam in India. The students were 541 (67.6%) males and 259 (32.4%) females in the age range of 17–20 years (Median age = 18.2 years, SD = 1.0). Results: On average, students engaged in 15.8 out of 25 health behavior practices. There was a high rate of overweight and obesity (26.8% and 10.7%, respectively), low rate of brushing teeth at least twice a day (28.6%), annual dental check-up (25.8%), habitual seatbelt use (23%), and poor dietary patterns (79% ate less than the recommended fruit and vegetable consumption of five servings a day, and 68.5% did not avoid eating fat and cholesterol). In multivariate analysis among men, personal constraints (Odds Ratio = OR 1.75, Confidence Interval = CI 1.09–2.82), health benefits (OR = 2.01, CI = 1.27–3.17), and not suffering from depression (OR = 0.60, CI = 0.22–0.94) were associated with the health behavior index. Among women, those who were living away from their parents or guardians (OR = 1.94, CI = 1.06–3.55), economically better off (OR = 2.16, CI = 1.00–4.63), and had higher social support (OR = 3.65, CI = 1.75–7.63), were associated with the health behavior index. Discussion: Students had a high proportion of health behavior practices. Several high health risk practices were identified, including overweight, poor dental practices, poor dietary and sleeping habits. It is hoped that the gender-specific predictors identified, including sociodemographics as well as social and mental health variables, can also be utilized in designing health promotion programs.
Keywords: health behavior; health benefits; health risk knowledge; India; university students. *Corresponding author: Professor Karl Peltzer, HIV/AIDS/SIT and TB (HAST) Research Program, Human Sciences Research Council, Private Bag X41, Pretoria 0001, South Africa, E-mail: [email protected]; Department of Psychology, University of Limpopo, Turfloop Campus, Sovenga, South Africa; and ASEAN Institute for Health Development, Madidol University, Salaya, Phutthamonthon, Nakhonpathom, Thailand Supa Pengpid: ASEAN Institute for Health Development, Madidol University, Salaya, Phutthamonthon, Nakhonpathom, Thailand; and University of Limpopo, Turfloop Campus, Turfloop, South Africa Krishna Mohan: Psychguru Mental Health Services, Palem, Madhurawada, Visakhapatnam, India; and University of Flores, Buenos Aires, Argentina
Introduction Chronic diseases, including heart disease, stroke, cancer, and diabetes are, by far, the leading causes of death worldwide, including India (1). Behavioral risk factors, including tobacco smoking, alcohol drinking, physical inactivity, sedentary behavior and obesity, are major determinants of adult chronic diseases morbidity and mortality (2–4). For instance, nearly 80% of incident cases of cardiovascular disease and Type II diabetes are attributable to physical inactivity, tobacco smoking, and unhealthy diet (1). In addition to the burden of disease attributed to single chronic behavioral risk factors, a growing body of evidence also suggests that behavioral risk factors (including physical inactivity, sedentary behavior, smoking, alcohol use, and obesity) co-occur among youth (5), and that their combinations yield greater risks for chronic diseases than the sum of their individual independent effects (6, 7). Health behaviors that are formed during childhood and adolescence can have a significant impact on the occurrence of future illnesses (8, 9). Many risk processes that lead to chronic non-communicable diseases in later life, including tobacco, alcohol, and illicit substance misuse,
Brought to you by | University of Connecticut Authenticated Download Date | 5/27/15 2:10 AM
532 Peltzer et al.: Health behavior unsafe sex, obesity and lack of physical activity, typically emerge around this time (9–11). Few studies among university students in India have shown health behavior risks, such as tobacco use [7% (12), 1.7% (13), 5.3% (14), 25.1% (15), 18.3%–43.6% (16), 45% (17)], lack of physical activity [42.6% (12), 35.2% (18), 79.8% (13), 57.6% (19)], recommended at least five servings per day of fruits and vegetables [12% (12)], alcohol use [28.8% (12)], cannabis use [4.5% (20)], and overweight [17.8% –29.6% (19)]. Factors identified to be associated with health behavior include sociodemographic factors [female gender (21–26), socioeconomic status (27–29), educational achievement (30, 31), social factors [social support (32), sense of coherence (25, 33, 34), religiosity or spirituality (32, 35), sense of control (36, 37)], and health variables [risk awareness (36, 38), perceived health benefits (36, 39, 40), low depression (41), low levels of psychological distress (42, 43)]. The purpose of this study was to assess the prevalence of health behaviors and its associated factors in a sample of Indian university students.
Materials and methods Sample and procedure The sample included 800 university students from non-health (mainly engineering and sciences) courses chosen at random from the Institute of Technology and Institute of Sciences at Gitam University in India. Data were collected by a self-administered questionnaire in a classroom situation after informed consent was obtained from the participants. Permission to carry out the study was obtained from the senior faculty of the university. Ethical clearance was also obtained. The cover page of the questionnaire briefly explained the objectives of the study, provided instructions to the respondents on how to fill it up, and gave information about the researchers. It also mentioned that anonymity and confidentiality would be maintained and that the participation of students was voluntary. Finally, it specified that the collected data would be used only for research purposes.
Measures Health behavior variables Tobacco use was assessed with the question: “Do you currently use one or more of the following tobacco products (cigarettes, snuff, chewing tobacco, cigars, etc.)?” Response options were “yes” or “no” (44). Alcohol consumption was measured by asking participants as to which of the following terms best described them: non-drinker, special occasions drinker, occasional drinker, and regular drinker. Occasional and regular drinkers were asked about how many days
over the last two weeks they had had a drink, and how many drinks they had consumed on those days. These data were used to derive four categories of alcohol consumption: none, very occasional, fewer than one drink per day, and more than one drink per day over the past 14 days (36). Illicit drug use was assessed with one question, “How often have you taken drugs in the past 12 months; other than prescribed by the health care provider?” Response options were 1 = 0 times to 4 = 10 or more times. Physical activity was assessed using the International Physical Activity Questionnaire (IPAQ) short version, self-administered last 7 days (IPAQ-S7S). We used the instructions given in the IPAQ manual for reliability and validity, which was detailed elsewhere (45). To sum up the single indicators to an overall indicator of PA-related EE (Metabolic equivalent, MET min–1) is a major goal of the IPAQ instruments. In accordance with the recommendations, we followed MET estimates of IPAQ: Vigorous PA = 8 METs, moderate PA = 4 METs, and walking on average = 3.3 METs. For calculating the overall METs PA, each category was multiplied with its special MET estimate value. We also used the recommended categorical score, which referred to three levels of PA (low, moderate, and high) as proposed in the IPAQ Scoring Protocol (short form). Low activity represented individuals who did not meet the criteria for moderate and vigorous intensity categories (
