Table 1. Demographic data of the participants.
was 19.22 (2.06 SD) while it was 22.45 (1.41 SD) in case of fourth-year students. The mean age of male respondents was 21.08 ± 1.5 years (range 17 - 32 years). The mean age of female respondents was 19.92 ± 1.46 years (range 17 - 24 years).
The mean and standard deviation of the total health promoting behaviors were 2.60 ± 0.29 out of a score of four. The result also indicated that the status of the health promoting behaviors among 142 students (64.9%) were relatively good (mean score range 2.5 - 4) and remaining 77 students were poorer.
The highest level of health promoting behaviors related to spiritual growth with a score of 2.99 ± 0.42. This was followed by interpersonal relations with 2.90 ± 0.35, stress management with 2.61 ± 0.44, nutrition with 2.44 ± 0.41, health responsibility with 2.39 ± 0.39 and physical activity with 2.25 ± 0.54 respectively (Table 2).
The first year students showed higher scores for overall HPLP at 2.65 ± 0.26, spiritual growth at 3.12 ± 0.38, and stress management at 2.54 ± 0.41 but other domains were not higher than that for the students in other years (Table 2). Second year students got the lowest overall score at 2.52 ± 0.31. The fourth year students were weakest in interpersonal relations. A significant difference was noted in between the various years in the domains of spiritual growth and stress management.
Table 3 shows segregated data on the basis of sex, residence type and school background. Differences were observed in the total HPLP scores and sub-scale scores between subgroups of participants’ characteristics. The males had an overall HPLP mean score of 2.62 ± 0.29, while the females had an overall HPLP mean score of 2.58 ± 0.29. The rural students had an HPLP score of 2.62 ± 0.28, while urban students had a score of 2.59 ± 0.30. The result asserted that students having a rural residence background are better in overall HPLP except nutrition. There was a significant association with the type of school and HPLP with the score being higher (2.69 ± 0.41) in those with a public school background compared to those with a private school background (2.54 ± 0.44).
Table 2. Mean distribution of Health Promoting Lifestyle Profile II (HPLP-II) scores according to year.
The values are expressed as means ± SD, and one-way analysis of variance (ANOVA) and multiple comparison procedures using the LSD test were conducted.
Table 3. Distribution of Health Promoting Lifestyle Profile (HPLP) scores according to gender, residence type, school background and higher education.
The values are expressed as means ± SD, and t-tests were conducted. *P < 0.05.
The two-sample correlation analysis averred that there were significant differences found between groups of gender, residence type and school background in the physical activity subscale. In addition, there was significant difference between respondents having a background of public and private school in the domains of health responsibility (p = 0.036), physical activity (p = 0.004) and stress management (p = 0.014) along with overall HPLP (p = 0.015). The health responsibility score was also significantly different between those who underwent higher secondary school compared to those who carried out proficiency certificate level in allied health sciences (p = 0.048).
Multiple regression analysis of the six personal variables with the overall HPLP score and six health-promoting lifestyle subscales scores was performed to determine which independent variables were good predictors of a healthy lifestyle in the participants. With all six variables in the regression model, the variance in the participants of health responsibility, spiritual growth, physical activity, interpersonal relation, nutrition, stress management and overall HPLP contributed 5.4%, 3.0%, 6.6%, 1.5%, 3.6%, 6.7% and 3.1%, respectively (Table 4).
A comparison of the frequency of students with the poor and relatively good HPLP across various demographic categories (Table 5) revealed that students from public school background have relatively good HPLP than that of private school background whereas no significant association was found between demographic variables like gender and residence type with health lifestyle behavior scale scores.
Patan Academy of Health Sciences (PAHS) enrolls students based on the “Social Inclusion Matrix (SIM)” to address social accountability and inclusiveness in the spirit of PAHS Act  as well as the Constitution of Nepal. That system has encompassed gender, school background (community/public), educational background (higher secondary; 10 + 2 and proficiency certificate level in allied health sciences) and place of permanent residence (rural and urban). Additionally, there are three provisions to get preference for admission which are; “ultra poor”, “rural resident” and “grades 8, 9 and 10 in community school”. PAHS has offered three categories of fee payment schemes namely “no pay”, “half pay”, “full pay” so as to enable socially and economically disadvantaged applicants to study medicine if they get selected. In addition, 5% students that have been enrolled are from Allied Health Sciences background which is not in practice in other medical schools in Nepal. The representation of public or community schools with 44.7% students at PAHS was due to SIM. This enabled our study to assess the role of the various demographic variables like school background, educational background and place of permanent residence with the HPLP scores.
The data showed that the overall HPLP score of respondents is 2.60 ± 0.29 which is relatively good. A HPLP of greater than 2.5 is considered to be good.
Table 4. Independent baseline predictors of health-promoting lifestyle profile II (HPLP-II) and demographic data of participants.
Table 5. Distribution of health lifestyle behavior scale scores of students.
Similar results have been reported in a study on medical students from other universities     .
Students in the first year of medical school reported good health promotion lifestyles which declined in the students in other year groups. They have obtained the highest score on spiritual growth with a mean of 3.12 and lowest score on physical activity of 2.24 out of a scale of 4. The fourth year students were weakest in interpersonal relation which we thought was a strange finding because students are engaged in community based learning and education activities as a part of curricular activities and have to work and interact with patients, health-centre staff and rural people in their communities many times during their training.
The study revealed that highest mean scores of HPLP among the six health- promoting lifestyles were for spiritual growth and interpersonal relations whilst the lowest scores were for health responsibility and physical activity which is comparable with data from a high income region in Asia  . This finding is also consistent with other studies     . Nepal is a culturally rich country where multiple religions co-exist, chief of them being Hinduism and Buddhism with small numbers of Muslims and Christians. Not only the older generation but the young also engage in prayers, God-worship and cultural rituals.
The score of health responsibility was poor (<2.5 mean score), which was contradicting with the results of studies conducted by Lee et al.  Montazeri et al.  , and Adderley-Kelly et al.  .
Additionally, the mean score of health promoting behaviors was higher among male respondents than that among the female, which was chiefly due to the greater score obtained by males on domain of physical activity. This was slightly different from the results of studies carried out by Díez et al. on Mexican students  , Stock et al. on German students  , and Von Bothmer et al. on Swedish students  . This hints at the cultural differences with respect to Nepali women where female students are less involved in sports or other physical activities compared to men. It also points to a need for more women-friendly sports and physical activity infrastructure in educational institutions and cities in Nepal.
It is known that demographic factors like age, residence type, education and school background have great role in determining health behaviors  . Urbanisation and access to transportation is greatly increasing throughout Nepal which means people have to walk less and do less physical work. The work of people is also shifting from the traditional manual labour, especially in agriculture, to other modes largely due to mechanization and also due to the increase in opportunity in services and trade. Our study shows that the physical activity scores are lower which is also a reflection of larger society in general.
This study also showed that physical activity and nutrition were the biggest predictors of healthy lifestyle in this student population. These domains are easily amenable to education, behavior change and other interventions like provision of commodities and infrastructure.
This study clearly shows that there is ample room for improvement in the health promoting lifestyle practices of medical students at PAHS and this could be representative of the students’ population and youth over much of Nepal and also in the South Asian region. The low score in physical activity and health responsibility demands an intervention from both campus administration and public health authorities at a wider level. A healthy lifestyle must be a part of the curriculum and efforts must be directed to ensuring infrastructure and services towards creating a healthy lifestyle.
We were limited by the fact that this study collected data only from one university status educational organization with bachelor level medical students. These findings may not be generalizable to all students or all young adults. Therefore, a larger study of this type with a more representative sample of all university students, young adults or the general population should be carried out. Such a study should explore health promotion behaviors, study style, social environment or activities, and physical activities, nutrition and daily lives.
In general, the results of the present study revealed that the status of health promoting behaviors was of an acceptable level with ample room for improvement among the students at Patan Academy of Health Sciences, Nepal. In this study, physical activity and nutrition are the largest predictors of the lifestyle and they need to be modified for the subgroups where the scores are low. The necessity of the implementation of health education and promotion programs with an emphasis on different dimensions of health lifestyles behaviors is recommended. According to this study, a good number of medical students are not adopting health promoting lifestyle behaviors on daily basis and their life-style behaviors are low in the mirror of graduate competency of the Patan Academy of Health Sciences. Thus, the researchers would like to recommend that Academy and faculty can facilitate student learning about health and link this to living a healthy lifestyle. By ‘‘learning health’’ to ‘‘live health’’ future doctors can design appropriate programs that will provide a much-needed gamut of proven strategies to help others attain and maintain healthy lifestyles.
We are grateful to all students who participated in this study for their kind support and cooperation.
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