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Factors that influence dietary behavior toward iron and vitamin D consumption based on the theory of planned behavior in Iranian adolescent girls

Nutrition Journal volume 18, Article number: 8 (2019) Cite this article

Abstract

Background

The impact of iron and vitamin D supplements among adolescent is not well understood. The prevalence of supplement use, and the behavioral intentions of adolescents was studied to better understand the data on supplement intake. We used the theory of Planned Behavior (TPB) to explore the determinants that influence supplement intake, and its potential constructs to examine determinants that influence dietary supplement behavior towards the use of iron and vitamin D supplements amongst a sample of Iranian schoolgirl.

Methods

This was a cross-sectional study of 485 adolescent girls aged 12–17 years. Multiple analytical models including hierarchical regression and structural equation modeling (SEM) were used to examine the association between TPB constructs and adolescent’s behavioral intentions to consume dietary supplements.

Results

Based on the results of SEM, constructs of TPB and knowledge were found to predict 74% of the variation in the behavioral intentions of the schoolgirls. SEM indicated that perceived behavioral control (PBC) and knowledge had significant associations with intention behaviors to take nutritional supplements.

Conclusion

TPB and its constructs were used to establish the determinants of iron and vitamin D intake among schoolgirls in Iran. This outcome indicates that efforts to promote behavioral intentions through targeting subjective norms, attitude, and PBC may promote supplement use.

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Background

Children who are entering adolescence need to consume adequate dietary micronutrient because they are going through many significant physical and intellectual changes [1, 2]. Several studies have reported that adolescents who consume a diet rich in micronutrients, have a lower risk of and cardiovascular diseases than those with a dietary pattern that is high in animal proteins, carbohydrates and fats, and lower in micronutrients [3,4,5]. The transition to adulthood is also considered to be a critical time for dietary intervention to improve long-term health behavior and responsibility for diet [6]. Previous studies have indicated that dietary interventions can improve long-term health behavior and lead to periodic changes in nutritional intakes and dietary behaviors in adulthood [7,8,9].

Deficiencies of iron and vitamin D are common in the adolescent population, which can have a negative impact during phases of rapid growth, increasing susceptibility to infection, autoimmune and other chronic disease and also impair mental development and learning [10, 11]. Dietary iron is mostly present in animal products (e.g red meat, fish, egg), certain plant foods and legumes. The main sources of vitamin D include dairy products, egg yolks, seafood and fruit juices. Numerous studies have identified an association between poor iron status and low Vitamin D concentration. Vitamin D deficiency is associated with an increased risk of deterioration of iron status and anemia [12,13,14]. It has been hypothesized that vitamin D may influence iron metabolism and erythropoiesis, while iron, in turn, is essential for the synthesis of vitamin D [12, 13].

According to the National Family Health Survey in Iran, 14–18% of girls suffer from iron deficiency anemia and 31% were reported to have insufficient iron stores [15]. In Iran, 14% of adolescents under the age of 18 suffer from iron deficiency anemia [16,17,18,19]. Current estimates indicate that vitamin D insufficiency/ deficiency is a common health problem, affecting 1 billion people globally, and 40–100% of European and American elderly men and women suffer from these deficiencies [20, 21]. The results of the meta-analysis study in 2018 in Iran indicated that the prevalence of vitamin D deficiency in men, pregnant women, and all women was respectively 46, 60, and 62% [22]. Whilst there may be sufficient levels of sunlight in Iran, the high prevalence of vitamin D deficiency may due to the types of clothing worn, dietary habits (low consumption of dairy products and seafood), lifestyle, air pollution, and skin pigmentation [21]. Numerous studies have shown that prevalence of vitamin D deficiency among women population is higher than for men in Iran [23,24,25]. This has been explained in terms of social obligations and cultural aspects. In Iran, women and girls (age > 9 years) are instructed to dress with full body covering that is usually dark and solid in coloration. This degree of covering allows for the entire face to be revealed, while continuing to cover the hair by wearing a scarf. Studies have indicated that skin covering is an important risk factor for vitamin D deficiency because it limits exposure to the sun and the level of vitamin D absorption [23,24,25].

To combat vitamin D and Iron deficiency in Iranian adolescents, a national program of supplements of iron and vitamin D is being conducted routinely in Iranian high schools for female students by the Health ministry. According to this program, 16 iron pills (Iron (II) fumarate), and 9 pearl vitamin D3 are given to students weekly and monthly, respectively. Despite, several studies that have shown that the positive effect of this supplementation programs (WIFS) in reducing the rate of vitamin D and Iron deficiency, a national report showed that the prevalence of anemia and vitamin D deficiency among Iranian adolescents remains high, and this may be explained by the refusal of adolescents to take these supplements [15, 22, 26,27,28]. Although efforts have been made to modify supplementation programs in Iran, the effect of behavioral intentions and attitude toward Iron and vitamin D intake have not been studied systematically, especially with respect to high-risk groups. It is still unclear what/how potential determinates can affect/impact adolescent’s attitude and intention to regular intake Iron and vitamin D [15, 16, 29, 30].

In recent decades, theories of public health have been developed to improve the health promotion behaviors to use food supplements among adolescent [31]. The theory of planned behavior (TPB) is a practical theoretical perspective to evaluate factors influence individual’s decision to engage in an specific behavior [32,33,34]. This theory links an individual’s attitude and behavior, and states that attitude and belief toward behavior, PBC, and subjective norms, together shape an individual’s intentions to engage actual behavior at specific place and time [35,36,37,38]. Therefore, in this study, we hypothesized that TPB could be a fundamental framework to identify and explain the main determinants that may affect iron and vitamin D supplement intake in Iranian girls. With a view to providing a basis for future studies, we aimed to (1) test the fit of the TPB; (2) to explore potential determinants that influence dietary behavior toward iron and vitamin D supplementation in female adolescents; and (3) to estimate the extent of the relationship between supplementation knowledge, attitude, subjective norms, and perceived control of behavior and intention towards intake of vitamin D and iron supplements.

Methods

Study population and sampling technique

This cross sectional study was conducted on 485 female high school students from Gonabad city (a city in the southeastern province of Khorasan Razavi, Iran) in 2017. We divided the city into 8 regions based the existence of high schools and population density. We then used random sampling to select 16 schools from 32 school and all students in these selected high schools were considered for recruitment if they (a) were able to complete all questionnaires; (b) had normal physical health; (c) could speak and read Persian language (their native language); and (d) lived in Gonabad city over the previous six months. Students were excluded if they unwilling to participate or were unable to give informed consent; had suffered mental disturbance, upper limb disability, and visual impairment. A total of 485 student age 12–17 were involved in this study. Among all participant invited to take part, 5 refused to participate and 480 students were finally included in the data analysis. We explained any unclear questions and informed all participants concerning the aim of this survey. All eligible students gave written informed consent.

Data collection

Data was collected by questionnaires that consisted of three parts: a) Demographical properties questionnaire b) Knowledge evaluation questionnaire c) supplement assistance of iron and vitamin D using the constructs of the TPB questionnaire.

The evaluation and validation of the questionnaire was conducted based on the comments of the group of experts (3 nutrition experts, and 5 health education experts), Content Validity Ratio (CVR) and Content Validity Index (CVI) were calculated. The CVR and CVI of the questionnaire were 0.90, which was acceptable. The questionnaire was used in a pilot study of 50 students to make sure that the questions were clear and understood by the girls, and the average of Cronbach’s alpha was 0.88 for all the structures of the planned behavior theories which was acceptable.

The questionnaire of demographic factors included student’s age, parents’ age, residence, and the parents’ employment status and education level, were reported by the participants in a self-reported questionnaire.

We designed a new questionnaire to examine the effect of potential constructs of TPB and knowledge on adolescent consumption behaviors. This questionnaire consisted of 27 questions that examined knowledge and items from the TPB (Azjen, 1991). To measure the level of knowledge, 9 questions were designed to examine what adolescent knew about the importance of iron and vitamin D supplements, and their effect on health outcome. These question were answered using a two-dimensional scale (right = 1, wrong = 0) [37, 39, 40].

The last 18 questions examined attitude, PBC, subjective norms and behavioral intention together affect Iron and vitamin D intake. To measure these constructs, the Likert scale had five options from strongly agree to strongly disagree. Further details related to questionnaire and their items were summarized into Table 1.

Table 1 Component loading of the adolescence dietary supplement knowledge and behaviors based on theory of planned behavior
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Statistical analyses

We used SPSS software (version 22) to analyze the data to provide descriptive data, and a multivariate model. Data were also tested by maximum likelihood estimation of a confirmatory factor analysis (CFA) method using the AMOS software for Windows, version 24. The CFA analysis allowed an assessment of the adequacy of the TPB and its constructs to present the process was surveyed and to estimate association among constructs (knowledge, attitude, perceived behavior control, subjective norms, and behavior intention). The evaluation of the model was conducted using fit criteria for the following indices: chi duo square Indicators (x2), Chi duo square ratio to degree of freedom (x2/df), root mean square error of approximation (RMSEA), adjusted goodness of fit index (AGFI), goodness of fit index (GFI), non-normed fit index (NNFI); parsimonious normed fit index (PNFI), and partnership intention (I) [41]. The model was considered to be a good fit if the (x2/df) < 5, RMSEA ≤0.08, SRMR < 0.05, AGFI > 0.8 and other indices (NFI, GFI, TLI) more than 0.9 [41, 42].

Results

Socio-demographic characteristics

The mean (standard deviation) for students’ age, father’s age, and mother’s age were 12.76 (0.63), 43.32 (5.64), and 39.22 (5.41) years respectively. In total, 329 (68%) of the students were residents of the city and 151 (32%) were residents of the surrounding villages. Most of parents (74%) had a diploma degree. 72% of students’ fathers were self-employed and 83% of mothers were housewives (Table 2). According to the regression model, socio-demographic variables accounted for 2.3% of the variance of behavioral intention. In this population, only residency location and father’s age were found to be associated with behavioral intention at the significance level of 0.05 (Table 3).

Table 2 Frequency distribution of student demographic factors
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Table 3 The results of linear regression analysis in predicting behavioral intention of using iron supplements and vitamin D based on demographic variables
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Model testing

Before conducting the analysis of the verified factor, the data for outliers and the normality of variables were examined, and the outlier data of each observation were analyzed by Mahalanobis distance and if necessary were omitted [43]. In the analysis of critical ratio of skewness or kurtosis of the variables, and the state of being multi- variable normal was verified, and as a result, a maximum likelihood method was conducted to estimate the parameters [44].

After performing the CFA analysis test, the knowledge (9 questions), attitude (4 questions), perceived behavioral control (PBC) (5 questions), subjective norm (6 questions) and behavioral intention (3 questions) remained in CFA. The goodness of fit for the measurement of CFA was acceptable (X2/df = 2.17, RMSEA = 0.04, AGFI = 0.89, GFI = 0.91, PNFI = 0.64, PCFI = 0.73) (Table 4).

Table 4 Models’ evaluation overall fit measurements
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To analyze the relationship between the four exogenous constructs (knowledge, attitude, PBC and subjective norm) and endogenous construct (behavioral intention), the structural equation modeling (SEM) was used.

The assessment of the SEM showed a good fit of indices: X2/df = 2.57, RMSEA =0.05, AGFI =0.87, GFI =0.90, PNFI =0.60, PCFI =0.67 (Table 4, Fig. 1). In summary, planned behavior theory and the knowledge structure explained 0.74 (with Confidence intervals 99% is 0.683–0.788) of the variance in the students’ behavior intention to take an iron supplement and vitamin D (Fig. 1). In summary, the results suggested that, there was significant direct effect of attitude (standardized path coefficient (SPC) =0.18, p < 0.05), subjective norm (SPC = 0.15, p < 0.05), and PBC (SPC = 0.83, p < 0.001) on behaviors intention, indicating about 82% of the total effects on behavior intention. Likewise, there was a significant indirect effect of knowledge (SPC = 0.34, p < 0.001) through enhancing PBC with 18% of the total effects on student’s intention (Fig. 1, Table 5). Among all constructs of planned behavior theory, PBC constructs were the strongest determinant (p < 0.001) for behavior intention compared other constructs, indicating about 44% of the total effects on behavior intention (Table 5).

Fig. 1
figure 1

SEM and Path coefficient between variables (*p < 0.05, **p < 0.001)

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Table 5 Direct and indirect effects of theory of planned behavior constructs and knowledge
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Discussion

This study examined the effects of psychosocial characteristics and individual’s knowledge on adolescent’s intentions to use iron and vitamin D supplements in Iran. Our results showed that socio-demographic variables had no significant effect on behavioral intention. Similar findings were reported previously which found that demographic characteristics exerted little effect on the intention behaviors [37, 40, 45].

Our finding suggests that an individual’s knowledge toward dietary vitamin D and Iron was moderate (4.58 from 9) (Table 1). Most adolescent (60%) in present study were aware of the potential health outcomes (such as calcium absorption, intelligence quotient, and delayed physical growth) associated with Iron and vitamin D deficiency. Likewise, our results showed that most of adolescents (> 50%) were not aware of some preventive effects of vitamin D and Iron supplementation (e, g., anemia and the immunity of the body) common in old age, and the focused on the here and now. This finding were in line with several studies on young adults and adolescents, who have been considered as “young invincible” because of their disregard for future health consequences [46, 47].

Furthermore, testing SEM helped to explain that total effects of knowledge resulting from significant indirect pathways. Our findings showed that indirect effects of individual’s knowledge were negatively mediated by perceived behavior control. The majority of previous studies reported the direct routes of individual’s knowledge on intention behaviors, failed to observe indirect effects [37, 48, 49]. This present work lends some support to the results of an American women and Canadian young adults studies performed by Heather Petraszko (2013) and Goodman (2015), who observed the effects of individual’s knowledge on behavioral intention could be mediated through constructs of perceived behavior control [37, 40].

The results from testing SEM showed good fit between the constructs of TPB and data, indicate all the significant paths were in the expected direction as it was reported by Heather Heather Petraszko (2013) and Goodman (2015) on the frequency of nutrition multivitamin/mineral use among American and Canadian young adults [37, 40]. Interestingly, our finding showed that the constructs of TPB are able to explain 74% of total variance of individual’s intention to use iron and vitamin D supplements. This is in agreement with several studies utilizing the application of TPB to predict nutrition and dietary supplements [48, 50]. Hagger et al. (2010) indicated the predictive relationships between key construct of TPB (i.e., attitude, subjective norms, PBC, intentions) and young adult’s intention to use multivitamin/mineral as well as the frequency of supplementation [51]. Ajzen have suggested that TPB as an appropriate choice to predict and explain people’s intentions and behavior to use fruit, vegetable and nutrition intake [50, 52].

Among all the constructs in this study, PBC emerge as the strongest direct path of intention, that mediates the effects of knowledge on individual’s intention to use dietary supplements among adolescents. Our finding suggests that adolescent who have a higher perception and cognition, show a greater intention to engage in iron and vitamin D consumption on a regular basis despite various conflicting situations. This is consistent with TBP assumptions and other similar studies that have indicated perceived difficulty or ease of performing the behavior significantly influence the individual’s intention to perform the behavior [50, 53, 54].

In present study, attitude positively affected individual’s intention, which was consistent with the TPB. Significantly, around 60% of participants either disagreed or strongly disagreed with the specific attitude statements include “getting enough iron and vitamin D through food and I do not need to eat supplements”. Likewise, close to half of participants believed that these supplements do not cause serious health problems in their body. Thus, most of participants possessed a positive sense and belief concerning the benefits of consumption of dietary supplements. However, some subjects (32%) believed that the use of supplements is harmful for their body and should be provided through food intake. A number of studies have found evidence that a high positive sense and attitude toward healthy behaviors is more likely to promote an individual’s intention regarding personal goals, such as supplement use [37, 51, 53].

We found that subjective norms positively affected intentions; accounting for 13–15% of the explained variance. Our finding indicates that friends, fathers and teachers had a great influence, by acting as role models and giving social support. This result was consistent with other studies that reported social influences, such as parents; friends and family doctors could potentially lead to long-term changes in adolescent’s intentions and behavior [50, 52, 53].

Regarding the main strength in this study is that it is one of the first to generate new finding to identify the potential determinant of supplement consumption among adolescent population, using TPB constructs. Examining the application of psychological theories in different population is important to understand the potential predictors in health promotion behaviors. Furthermore, we explored the factor constructs to find out how they influence intention behavior. This is essential approach for each successful investigation since it provides useful information about the potential constructs that influence individual’s intentions to engage the healthy behavior at specific time,

This study is not without limitations: however, these shortcomings explained here can be applied as guide for other studies in future. Our participants were selected from female adolescent population (aged 12–17) who were living in Iran. Our findings may not be generalizable to younger or older population. Secondly, this result generated from strategies in present study to regular intake Iron and vitamin D information may not be applicable for other dietary supplement, with long-term health implications such as omega-3 and calcium. Therefore, future testing of the TPB with longitudinal data among other populations and dietary supplement would be useful to examine whether results are comparable.

Thirdly, although the use of self-reported questionnaire and a cross-sectional data is common in TPB assessment [53], it may have led to conceptual problems in the causal inferences of the TPB and let to over representation the associations among constructs of TPB. Thus, it must be noted that the predictors likely are less strongly associated with consumption of supplements among adolescent than what was observed in present study.

We acknowledge that this study would have been more effective if the education intervention had been conducted and its effect were measured in changing the adolescents’ intention and behavior. Thus, further study should focus on longitudinal data to assess effects of TPB-based interventions on changing young adolescents’ intention and behavior.

Conclusions

This study provides support for the effectiveness of TPB and its potential constructs in testing for the determinants of iron and vitamin D supplement intake among adolescent in Iran. We found that knowledge, subjective norms, attitude, and PBC could be potential determinates to explain and predict female adolescent’s intentions regarding vitamin D and iron consumption. PBC was the strongest construct of TPB at predicting people’s intentions to use iron and vitamin D.

Practice implications

This study suggested that an individual’s knowledge, attitude, subjective norms and PBC may influence the level of intention behavioral to intake dietary supplements. Identification of potential determinants that influence effective behavior change could be useful for health promoters and public health policy educators to better perceived adolescent’s needs and intention to intake dietary supplements.

Abbreviations

SEM:

Structural equation modeling

TPB:

Theory of planned behavior

References

  1. Allen LH, De Benoist B, Dary O, Hurrell R. Organization WH: guidelines on food fortification with micronutrients; 2006.

    Google Scholar 

  2. Shankar V, Gouda M, Moncivaiz J, Gordon A, Reo N, Hussein L, Paliy O. Differences in gut metabolites and microbial composition and functions between Egyptian and US children are consistent with their diets. Msystems. 2017;2:e00169–16.

    Article  Google Scholar 

  3. Eilat-Adar S, Sinai T, Yosefy C, Henkin Y. Nutritional recommendations for cardiovascular disease. Nutrients. 2013;5:3646–83.

  4. Buil-Cosiales P, Martinez-Gonzalez MA, Ruiz-Canela M, Díez-Espino J, García-Arellano A, Toledo E. Consumption of fruit or fiber-fruit decreases the risk of cardiovascular disease in a Mediterranean young cohort. Nutrients. 2017;9:295.

  5. Fathi A, Sharifirad G, Mohebi S. Evaluating the performance of unhealthy junk food consumption based on health belief model in elementary school girls. J Health Lit. 2017;2:45–53.

  6. Kaur S, Sangha JK. Effect of Iron supplementation along with vitamin C and nutrition counseling on the Anaemic status of adolescent girls. International Journal of Health Sciences and Research (www ijhsr org) ISSN. 2016:2249–9571.

  7. Gouda M, Moustafa A, Hussein L, Hamza M. Three week dietary intervention using apricots, pomegranate juice or/and fermented sour sobya and impact on biomarkers of antioxidative activity, oxidative stress and erythrocytic glutathione transferase activity among adults. Nutr J. 2015;15:52.

    Article  Google Scholar 

  8. Ahmed FE, Gouda MM, Hussein LA, Ahmed NC, Vos PW, Mohammad MA. Role of melt curve analysis in interpretation of nutrigenomics' MicroRNA expression data. Cancer Genomics-Proteomics. 2017;14:469–81.

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Solhi M, Jormand H, Gohari M. The Impact of Media Literacy Intervention on the Students\'Attitudes about Self-Medication of Slimming Supplements. J Health Lit. 2016;1:13–24.

  10. del Balzo V, Vitiello V, Germani A, Donini LM, Poggiogalle E, Pinto A. A cross-sectional survey on dietary supplements consumption among Italian teen-agers. PLoS One. 2014;9:e100508.

    Article  Google Scholar 

  11. Gallagher CM, Black LJ, Oddy WH. Micronutrient intakes from food and supplements in Australian adolescents. Nutrients. 2014;6:342–54.

    Article  Google Scholar 

  12. Fouad MT, Moustafa A, Hussein L, Romeilah R, Gouda M. In-vitro antioxidant and antimicrobial activities of selected fruit and vegetable juices and fermented dairy products commonly consumed in Egypt. Research journal of pharmaceutical biological and chemical sciences. 2015;6:541–50.

    CAS  Google Scholar 

  13. Gouda M, Zu L, Ma S, Sheng L, Ma M. Influence of bio-active terpenes on the characteristics and functional properties of egg yolk. Food Hydrocoll. 2018;80:222–30.

    Article  CAS  Google Scholar 

  14. Gouda M, Zhang S, Liu Y, Sheng L, Ma M. Effects of four natural antioxidant phenyl terpenes on emulsifying and rheological properties of egg yolk. LWT-Food Science and Technology. 2017;83:59–67.

    Article  CAS  Google Scholar 

  15. Kheirouri S, Alizadeh M. Process evaluation of a national school-based iron supplementation program for adolescent girls in Iran. BMC Public Health. 2014;14:959.

    Article  Google Scholar 

  16. Akbari M, Moosazadeh M, Tabrizi R, Khatibi SR, Khodadost M, Heydari ST, Tahami AN, Lankarani KB. Estimation of iron deficiency anemia in Iranian children and adolescents: a systematic review and meta-analysis. Hematology. 2017;22:231–9.

    Article  CAS  Google Scholar 

  17. Derman O, Öksüz-Kanbur N, Yenicesu İ, Kınık E: Iron deficiency anemia in a group of Turkish adolescents: frequency and contributing factors. De Gruyter; 2005.

    Google Scholar 

  18. Killip S, Bennett JM, Chambers MD. Iron deficiency anemia. Am Fam Physician. 2007.

  19. Rezaeian A, Ghayour-Mobarhan M, Mazloum SR, Yavari M, Jafari S-A. Effects of iron supplementation twice a week on attention score and haematologic measures in female high school students. Singap Med J. 2014;55:587.

    Article  Google Scholar 

  20. Hagenau T, Vest R, Gissel T, Poulsen C, Erlandsen M, Mosekilde L, Vestergaard P. Global vitamin D levels in relation to age, gender, skin pigmentation and latitude: an ecologic meta-regression analysis. Osteoporos Int. 2009;20:133.

    Article  CAS  Google Scholar 

  21. Hashemipour S, Lalooha F, Mirdamadi SZ, Ziaee A, Ghaleh TD. Effect of vitamin D administration in vitamin D-deficient pregnant women on maternal and neonatal serum calcium and vitamin D concentrations: a randomised clinical trial. Br J Nutr. 2013;110:1611–6.

    Article  CAS  Google Scholar 

  22. Tabrizi R, Moosazadeh M, Akbari M, Dabbaghmanesh MH, Mohamadkhani M, Asemi Z, Heydari ST, Akbari M, Lankarani KB. High prevalence of vitamin D deficiency among Iranian population: a systematic review and meta-analysis. Iranian journal of medical sciences. 2018;43:125.

    PubMed  PubMed Central  Google Scholar 

  23. Emdadi R, Chaichian S, Mahboubi M, Moradi Y, Akhlaghdoust M, Basharkhah A. Prevalence of vitamin D deficiency among women of reproductive age: a multi centric study in Tehran. Shiraz E-Medical Journal. 2016;17.

  24. Alagöl F, Shihadeh Y, Boztepe H, Tanakol R, Yarman S, Azizlerli H, Sandalci Ö. Sunlight exposure and vitamin D deficiency in Turkish women. J Endocrinol Investig. 2000;23:173–7.

    Article  Google Scholar 

  25. Batieha A, Khader Y, Jaddou H, Hyassat D, Batieha Z, Khateeb M, Belbisi A, Ajlouni K. Vitamin D status in Jordan: dress style and gender discrepancies. Ann Nutr Metab. 2011;58:10–8.

    Article  CAS  Google Scholar 

  26. Alipoor R, Gholami MS, Heidari-Soureshjani R, Reza Rajabi M, Anari MJ, Vaziri MS, Vajdi S, Shamshirian A. The prevalence of Iron deficiency Anemia among high school students in Iran: a systematic review. Internal Medicine and Medical Investigation Journal. 2017;2:1–6.

    Article  Google Scholar 

  27. Ebrahimi M, Khashayar P, Keshtkar A, Etemad K, Dini M, Mohammadi Z, Ebrahimi H, Chaman R, Larijani B. Prevalence of vitamin D deficiency among Iranian adolescents. J Pediatr Endocrinol Metab. 2014;27:595–602.

    Article  CAS  Google Scholar 

  28. Faghih S, Abdolahzadeh M, Mohammadi M, Hasanzadeh J. Prevalence of vitamin d deficiency and its related factors among university students in shiraz iran. International journal of preventive medicine. 2014;5:796.

    PubMed  PubMed Central  Google Scholar 

  29. Khammarnia M, Amani Z, Hajmohammadi M, Ansari-Moghadam A, Eslahi M. A survey of Iron supplementation consumption and its related factors in high school students in Southeast Iran, 2015. The Malaysian journal of medical sciences: MJMS. 2016;23:57.

    Article  Google Scholar 

  30. Vatandost S, Jahani M, Afshari A, Amiri MR, Heidarimoghadam R, Mohammadi Y. Prevalence of vitamin D deficiency in Iran: a systematic review and meta-analysis. Nutr Health. 2018:0260106018802968.

  31. O’dea JA. Consumption of nutritional supplements among adolescents: usage and perceived benefits. Health Educ Res. 2003;18:98–107.

    Article  Google Scholar 

  32. Oztekin C, Teksöz G, Pamuk S, Sahin E, Kilic DS. Gender perspective on the factors predicting recycling behavior: implications from the theory of planned behavior. Waste Manag. 2017;62:290–302.

    Article  Google Scholar 

  33. Ajzen I, Joyce N, Sheikh S, Cote NG. Knowledge and the prediction of behavior: the role of information accuracy in the theory of planned behavior. Basic Appl Soc Psychol. 2011;33:101–17.

    Article  Google Scholar 

  34. Siuki HA, Peyman N, Vahedian-Shahroodi M, Gholian-Aval M, Tehrani H. Health education intervention on HIV/AIDS prevention behaviors among health volunteers in healthcare centers: An applying the theory of planned behavior. J Soc Serv Res. 2018. p. 1–7.

  35. Cox DN, Koster A, Russell CG. Predicting intentions to consume functional foods and supplements to offset memory loss using an adaptation of protection motivation theory. Appetite. 2004;43:55–64.

    Article  CAS  Google Scholar 

  36. Pawlak R, Brown D, Meyer MK, Connell C, Yadrick K, Johnson J, Blackwell A. Theory of planned behavior and multivitamin supplement use in Caucasian college females. J Prim Prev. 2008;29:57–71.

    Article  Google Scholar 

  37. Petraszko H. Theory of planned behavior to predict multivitamin/mineral use; 2013.

    Google Scholar 

  38. Solhi M, Shirzad M. Situation of fruits and vegetables consumption in the dormitory female students based on the theory of planned behavior. J Health Lit. 2016;1:129–36.

  39. Ajzen I: The theory of planned behaviour. Organizational Behaviour and Human Decision Processes, 50, 179–211. De Young 1991, 50:509–526.

    Google Scholar 

  40. Goodman S. Vitamin D knowledge, perceptions, intake and status among young adults: a Validation & Intervention Study Using a Mobile ‘app’; 2015.

    Google Scholar 

  41. Lomax RG, Schumacker RE. A beginner's guide to structural equation modeling: Psychology Press; 2004.

  42. Kline R. Details of path analysis. In: Principles and practice of structural equation modeling. Guilford, New York; 2005. p. 123–64.

  43. De Maesschalck R, Jouan-Rimbaud D, Massart DL. The mahalanobis distance. Chemom Intell Lab Syst. 2000;50:1–18.

    Article  Google Scholar 

  44. Kaiser HF, Rice J. Little jiffy, mark IV. Educ Psychol Meas. 1974;34:111–7.

    Article  Google Scholar 

  45. Tavakoly Sany SB, Peyman N, Behzhad F, Esmaeily H, Taghipoor A, Ferns G. Health providers’ communication skills training affects hypertension outcomes. Medical teacher. 2018;40:154–63.

    Article  Google Scholar 

  46. Gooding HC, Sheldrick RC, Leslie LK, Shah S, de Ferranti SD, Mackie TI. Adolescent perceptions of cholesterol screening results:“young invincibles” or developing adults? J Adolesc Health. 2016;59:162–70.

    Article  Google Scholar 

  47. McDermott MS, Oliver M, Simnadis T, Beck E, Coltman T, Iverson D, Caputi P, Sharma R. The theory of planned behaviour and dietary patterns: a systematic review and meta-analysis. Prev Med. 2015;81:150–6.

    Article  CAS  Google Scholar 

  48. Menozzi D, Sogari G, Mora C. Explaining vegetable consumption among young adults: an application of the theory of planned behaviour. Nutrients. 2015;7:7633–50.

    Article  Google Scholar 

  49. St-Pierre RA, Temcheff CE, Derevensky JL, Gupta R. Theory of planned behavior in school-based adolescent problem gambling prevention: a conceptual framework. J Prim Prev. 2015;36:361–85.

    Article  Google Scholar 

  50. Ajzen I. The theory of planned behaviour is alive and well, and not ready to retire: a commentary on Sniehotta, Presseau, and Araújo-Soares. Health Psychol Rev. 2015;9:131–7.

    Article  Google Scholar 

  51. Hagger MS, Chan DK, Protogerou C, Chatzisarantis NL. Using meta-analytic path analysis to test theoretical predictions in health behavior: an illustration based on meta-analyses of the theory of planned behavior. Prev Med. 2016;89:154–61.

    Article  Google Scholar 

  52. Guillaumie L, Godin G, Vézina-Im L-A. Psychosocial determinants of fruit and vegetable intake in adult population: a systematic review. Int J Behav Nutr Phys Act. 2010;7:12.

    Article  Google Scholar 

  53. Bazargan-Hejazi S, Teruya S, Pan D, Lin J, Gordon D, Krochalk PC, Bazargan M. The theory of planned behavior (TPB) and texting while driving behavior in college students. Traffic injury prevention. 2017;18:56–62.

    Article  Google Scholar 

  54. Duncan MJ, Rivis A, Jordan C. Brief report: understanding intention to be physically active and physical activity behaviour in adolescents from a low socio-economic status background: an application of the theory of planned behaviour. J Adolesc. 2012;35:761–4.

    Article  Google Scholar 

  55. Navarra T. The encyclopedia of vitamins, minerals, and supplements: Infobase Publishing; 2014.

  56. Organization WH: Iron deficiency anaemia: assessment, prevention and control: a guide for programme managers. 2001.

    Google Scholar 

  57. Mark S. Vitamin D status and recommendations to improve vitamin D status in Canadian youth. Appl Physiol Nutr Metab. 2010;35:718–8.

  58. Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50:179–211.

    Article  Google Scholar 

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Acknowledgements

The authors would like to express their deepest appreciation to the students, managers, teachers, and staff in the Social Determinants of Health Research Center who assisted the authors to run this research project.

Funding

No financial support was received for this study.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Author information

Author notes

  1. Ali Alami and Seyedeh Belin Tavakoly Sany contributed equally as first author to this work.

Authors and Affiliations

  1. Department of Public Health, School of Public Health, Social Determinants of Health Research Center, Gonabad University of Medical Sciences, Gonabad, Iran

    Ali Alami

  2. Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran

    Seyedeh Belin Tavakoly Sany

  3. Department of Health Education and Health Promotion, Faculty of Health, Mashhad University of Medical Sciences, Mashhad, Iran

    Seyedeh Belin Tavakoly Sany

  4. Student Research Committee, Department of Public Health, School of Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Elaheh Lael-Monfared

  5. Department of Medical Education, Brighton and Sussex Medical School, Division of Medical Education, University of Brighton Falmer campus, Brighton, BN1 9PH, UK

    Gordon A Ferns

  6. School of Health, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran

    Maryam Tatari

  7. Department of health, Social Determinants of Health Research Center, Gonabad University of Medical Sciences, Gonabad, Iran

    Zahra Hosseini

  8. Social Determinants of Health Research Center, Gonabad University of Medical Sciences, Gonabad, Iran

    Alireza Jafari

  9. Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran

    Alireza Jafari

Authors
  1. Ali Alami
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  2. Seyedeh Belin Tavakoly Sany
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  3. Elaheh Lael-Monfared
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  4. Gordon A Ferns
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  5. Maryam Tatari
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  6. Zahra Hosseini
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Contributions

Authors AA and AJ designed the study. SBTS, ELM, GF, MT and ZH participated in the conception of the study. MT and AJ managed and conducted the statistical analyses and interpreted the data. AA and AJ wrote the first draft and SBTS, ELM, GF, MT and ZH revised it to make the final manuscript. All authors have approved the final manuscript.

Corresponding author

Correspondence to Alireza Jafari.

Ethics declarations

Ethics approval and consent to participate

This study is based on a research project approved by Ethics Committee of Gonabad University of Medical Sciences with the code of ethics IR.GMU.REC.1394.99. All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Alami, A., Tavakoly Sany, S., Lael-Monfared, E. et al. Factors that influence dietary behavior toward iron and vitamin D consumption based on the theory of planned behavior in Iranian adolescent girls. Nutr J 18, 8 (2019). https://doi.org/10.1186/s12937-019-0433-7

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  • DOI: https://doi.org/10.1186/s12937-019-0433-7

Keywords

Nutrition Journal

ISSN: 1475-2891

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