Effects of the nutrition education intervention on food security,anthropometry,and body composition in women: A randomized controlled trial

Abstract

Background

Food insecurity as a social determinant of health is associated with adverse physical health outcomes such as obesity.

Aim

This study aimed to evaluate the effects of nutrition education intervention based on the transtheoretical model (TTM) on food security, anthropometry, and body composition status.

Methods

In this randomized controlled trial, an intervention was conducted over months (five weeks) using the TTM among 160 women aged 19–64 years. Food security status, anthropometry, and body composition were determined three times: at baseline, three months, and six months after the intervention.

Results

In the intervention group, food insecurity significantly decreased before, immediately after, and six months after the intervention, these changes were significant in follow-up time and treatment effect. After six months of follow-up, the intervention group significantly decreased weight (−1.29 kg), body mass index (−0.54), and waist circumference (−3.48 cm). Although differences between the two groups were not statistically significant except in the interaction between follow-up time and intervention groups. Also, the mean of fat mass and total body water decreased in the intervention group and differences between the two groups were statistically significant in follow-up time (p < 0.001 and p = 0.01, respectively) and interaction between follow-up time and intervention group (p < 0.001 and p = 0.005, respectively).

Conclusion

In the current study, the findings of a six-month TTM-based intervention among women were positive that revealed to be a strategy that may improve anthropometric and nutritional status. Therefore, government programs that offer nutrition counseling should be prioritized to help the population to improve their eating habits.

Keywords

Anthropometric indices body composition food security stage-matched education transtheoretical model (TTM)

Introduction

Food insecurity as a serious public health problem in the past two decades affecting low-, middle-, and high-income countries around the world (Furness et al., 2004; Kohansal et al., 2019). According to World Health Organization reports, approximately 2.3 billion people worldwide (29.3%) experienced moderate to severe food insecurity in 2021, with the majority of these individuals living in developing nations (WHO, 2021). Food insecurity means limited or uncertain access to sufficient nutritious food through socially acceptable and safe ways (Anderson, 1990). Food insecurity as a social determinant of health is associated with adverse physical health outcomes such as weight status (Moradi et al., 2019). High rates of obesity and dependent diseases often co-occur with a lack of resources, poverty, and low community efficacy (Randhawa et al., 2020). Being slightly food insecure or not having enough to eat is actually linked to more weight gain than being fully food secure. There is evidence that low food security (LFS) is related to obesity due to the limited resources, time, and knowledge that populations with less LFS experience to engage in healthy eating and exercise (Dhurandhar 2016; Drewnowski & Darmon, 2005; Kendall et al., 1996). In addition, the evidence demonstrates that LFS affects body fat supplies, especially in low social status people (Dhurandhar, 2016).

The coexistence of obesity and food insecurity has been recognized in low-income settings and different ethnic minorities (Ballard-Barbash et al., 2013). By encouraging economic self-sufficiency in individuals and households, nutrition education can help people make the best use of their food budget by encouraging them to purchase healthy foods. Better financial management abilities reduce the likelihood of food insecurity in low-income households (Gundersen & Garasky, 2012). Worries about eating habits are not only in western countries but also in developing countries. In rapidly developing countries, nutrition transition, changes in food consumption with increasing intake of energy-dense western-style foods along with insufficient physical activity, leads to the increasing prevalence of obesity. More than one-third of people eat more than their needs and also eat low-nutrient-dense foods (Ghassemi et al., 2002; WHO, 2010).

To prevent obesity there is no well-established universal intervention, due to the complexity of the problem (Haynos and O’Donohue, 2012). Promoting eating habits and lifestyles may require people's improved awareness about the threats and consequences of the coexistence of food insecurity and obesity, but awareness is not enough. Because of the less efficiency of traditional health education interventions, to improve program effectiveness and efficacy new theory-based interventions should be performed within clear frameworks. Moreover, the implementation of training programs based on behavioral change models and theory-oriented approaches is needed in health interventions for promoting quality of life (Rabiollah, 2009; Prochaska, 2013; Sharma, 2011). The transtheoretical model (TTM) is one of the most useful theories in health interventions for behavioral change and promoting lifestyle. Despite the positive results already verified and the promising nature of TTM, the studies are usually conducted among middle and high-income populations in developed countries. The studies that were carried out using the model among low socioeconomic populations and under real situations such as public health services are scarce. Therefore, the aim of this study was to evaluate the effects of nutrition education intervention based on TTM to improve food security, anthropometry, and body composition status among Iranian women (Figure 1).

Materials and methods

Participants, study design, and sampling method determination

This randomized, controlled trial was conducted among women aged 19–64 years old living in Sardrood-Tabriz city, Iran from March to December 2017. The women were selected from two health centers in Sardrood, then to select households and areas at each health center were used a systematic random sampling method. The participants were recruited via a blending approach of cluster, random, and systematic sampling. The sample size based on the study by Mohammadi et al. (2008) and considering a 95% confidence level was calculated to be 70 subjects per each group. The first step of the study was descriptive and cross-sectional that was interviewed 192 women from each household. Finally, in the second step, from all 192 women who agreed to participate in the study, 160 women were selected for participation in the study and then randomized to the nonintervention comparison or the intervention groups (80 women in each group). The study process is presented in Figure 1.

Excluded criteria were migration, pregnancy, breastfeeding, following a diet for losing weight, or consuming drugs related to gaining weight. To identify women's sociodemographic characteristics, trained interviewers administered the pretested questionnaires in face-to-face interviews. The interviewers were educated previously and throughout the data collection process regularly controlled.

Ethical considerations

The study protocol was certified by the ethical committee of Tabriz University of Medical Sciences by reference number: IR.TBZMED.REC.1396.291. All the participants received a clear explanation of the study protocol before entering the study and signed informed consent.

Intervention

To make changes in household food security status, anthropometric indices, and body composition of participants an intervention was conducted over months (five weeks) using the TTM. After randomization, the intervention group was divided by stages of change and then the sessions were tailored to those stages of change and processes related to the stages of change.

The components of the interventions included practical nutrition workshops and interactive seminars. Each session was held for 60 min, once a week. In each session, audiences were taught about the following items:

- The food groups and their importance in health, especially in preventing obesity.

- The food pyramid and my plate.

- Food safety, healthy cooking methods, and how to prepare and cook delicious and low-calorie meals such as low-fat foods with a high number of inexpensive vegetables.

- How to use and interpret food labels.

- Food insecurity and its causes and consequences.

- Concept of energy balance.

Moreover, to enhance nutritional knowledge and change the attitudes and practices of participants, in each session, the positive outcomes of maintaining a healthy body weight and following a healthy diet were described.

During the first introductory session, the purpose, expectations, and importance of the study were described, and also food safety, body composition, and anthropometric indices were explained. Participants in the pre-contemplation stage completed the second session incorporating conscious raising (raising awareness about food insecurity, body composition, and unhealthy dietary behaviors) and dramatic relief (reacting emotionally to warnings about food insecurity, body composition, and unhealthy dietary behaviors). Women in the contemplation/preparation stage completed the third session with the incorporation of self-evaluation (one's self-image assessment with or without a particular unhealthy habit). The fourth session was planned to increase self-assurance and self-efficacy, help participants anticipate and overcome barriers, and improve skills in food management. During the fifth session, women received one educational CD, three brochures, and a handbook about comparing prices, shopping with a list, planning meals, thinking about healthy food choices, reading labels, and eating various foods to support women and their families. The action/maintenance stage includes a helping relationship (having a caring, accepted, and trusted person who can counsel and support the healthy behavior change), control of stimulus (countering or removing stimuli that elicit problem behavior), and management of reinforcement (being rewarded by others or rewarding oneself for making dietary change). After the study for ethical purposes, we held five lectures for participants in the comparison group and gave them one nutritional book.

Measures and assessments

A well-trained nutritionist that was blind to the allocation of the study collected data. The general questionnaire (about sociodemographic information) was filled at baseline once, but all other questionnaires were filled three times including two weeks before the intervention (baseline), three months after the intervention (middle), and six months after the intervention (the end of the study).

Household food security status

We evaluated the food security status of the households in the past 12 months, by sequences of questions considering food adequacy and financial limitations. The assessment was conducted using a locally validated, 18-item United States Department of Agriculture (USDA) Household Food Security Survey Module developed by the USDA Food and Nutrition Service to measure food insecurity and hungry (Rafiei et al., 2009). The module uses questions of an 18-item set that identifies if a selected behavior has occurred or during the last 12 months a targeted condition existed because of financial constraints. Of all items, 10 items refer to adults, while the remaining items focus on children in the household. The household food security status by the module categorizes into four classes as follows: high food security (HFS), marginal food security, LFS, and very LFS (VLFS) (Rabbitt et al., 2016).

Demographic and anthropometric measurements

Demographic data cover personal sociodemographic information including age, marital status, education, income, occupation, number of children, and family size. Body weight and height were measured in participants barefoot wearing minimal clothing by Seca digital scale and stadiometer, with the accuracy of ±0.1 cm and ±0.1 kg, respectively. Body mass index (BMI) was calculated as the weight in kilograms divided by the height in square meters (Raymond and Morrow, 2020). Waist circumference (WC) was measured at the narrowest point between the superior iliac crest and the lower costal margin and after exhaling by flexible anthropometric tape. Hip circumference (HC) was measured when the buttocks extended to the maximum. Waist hip ratio was obtained by dividing the waist size by the HC (Raymond and Morrow, 2020).

Body composition analyses

For body composition analysis including total body water (TBW), fat mass (FM), and skeletal muscle mass, we used a hand-to-hand impedance analyzer (OMRONBF511, Germany). In brief, all the women underwent body composition analysis in the morning after overnight fasting while wearing light indoor clothes. Before measurements, were requested of the women empty their bladders. The device was held while both arms were horizontally positioned in front of the body. Age, weight, height, and gender were given as input into the device (Mialich et al., 2014).

Stage of behavior change measures

We designed a reliable and valid TTM-based questionnaire for SOC for household food security status, anthropometric indices, and body composition of participants. In summary, we performed a qualitative study to create an item pool. Then, the questionnaire was assessed, revised, and modified by 15 nutritionists and health education specialists. Next, to provide a pre-final version of the questionnaire, content and face validity were conducted. The questionnaire was evaluated via a quantitative approach and in the quantitative phase, the validity and reliability (test–retest analysis and internal consistency) of the instrument were assessed. A pilot study was carried out on more than 10% of the study subjects to test and retest the questionnaire. A 10-item questionnaire was developed by the qualitative phase, which after content validity, it was reduced to a seven item. Finally, two items were removed and the five-item questionnaire was prepared for the main study. The test-retest reliability and Cronbach's alpha coefficients indicated excellent internal consistency (alpha = 0.73). This questionnaire consisted of a question were asked participants to choose the best-described statement of their status, with five statements that were categorized the participants into different stages of change including pre-contemplation, contemplation, preparation, action, and maintenance (Prochaska et al., 2013).

Statistical analyses

Data analyses were done by SPSS version 24. To obtain the household food security index, responses were scored according to the USDA Food and Nutrition Service criteria (Ajao et al., 2010). Descriptive variables such as the distribution of household food security and women's basic demographic characteristics were expressed as percentages and frequencies. Differences between the two groups were evaluated by an independent t-test, at the baseline of the study. The complete data sets were analyzed using Generalized Estimating Equations (GEEs) examination. GEE allows analysis of longitudinal data for both categorical outcomes and continuous repeated measures effects. All GEEs that were run with an unstructured variance matrix used the comparison group as a reference.

Results

The general characteristics of participants are presented in Table 1. A total of 192 women aged 38.6 ± 8.5 years were included in this clinical trial. For all variables between the two groups, there were no statistically significant differences at the baseline, except FM (%) and SOC in food security.

Table 1.

Baseline characteristics of participants in intervention and control group.

Variables	Total (N = 192)	Intervention group (N = 73)	Control group (N = 78)	p value
Age (year)	38.68 ± 8.51	38.68 ± 8.1	39.18 ± 9.5	0.73^a
Age of marriage (year)	19.41 ± 3.85	18.88 ± 2.7	19.44 ± 4.0	0.32^a
Age of household's supervisor (year)	43.53 ± 9.93	44.04 ± 9.3	44.33 ± 11.0	0.86^a
House square (m²)	105.68 ± 47.70	111.00 ± 55.2	109.62 ± 44.4	0.86^a
Family size	3.67 ± 1.02	3.52 ± 0.8	3.68 ± 1.0	0.29^a
Number of employees	1.09 ± 0.41	1.11 ± 0.3	1.06 ± 0.4	0.50^a
Number of children	1.93 ± 1.02	1.84 ± 0.9	1.95 ± 0.9	0.47^a
Weight (kg)	71.84 ± 10.85	73.61 ± 11.6	70.81 ± 10.5	0.12^a
BMI (kg/m²)	29.71 ± 4.53	30.57 ± 4.45	29.10 ± 4.64	0.05
WC (cm)	100.03 ± 10.31	101.22 ± 10.75	99.60 ± 10.60	0.35
FM (%)	43.15 ± 5.69	44.27 ± 5.14	42.26 ± 6.10	0.03
TBW (%)	44.92 ± 3.36	44.30 ± 2.94	45.32 ± 3.67	0.06
Home ownership				0.41b
Owns	156 (81.3%)	61 (83.6%)	61 (78.2%)
Doesn’t owns	36 (18.8%)	12 (16.4%)	17 (21.8%)
Occupation				0.52^b
House wife	172 (89.6%)	66 (90.4%)	67 (85.9%)
Part-time job	18 (9.4%)	6 (8.2%)	10 (12.8%)
Student	2 (1.0%)	1 (1.4%)	1 (1.3%)
Education				0.51^b
Primary school and below	93 (48.4%)	30 (41.1%)	38 (48.7%)
Secondary school	87 (45.3%)	38 (52.1%)	34 (43.6%)
Collegiate and above	12 (6.3%)	5 (6.8%)	6 (7.7%)
Households’ supervisor occupation				0.32^b
Jobless	18 (9.4%)	3 (4.1%)	12 (15.4%)
Worker	100 (52.1%)	39 (53.4%)	34 (43.6%)
Employee	11 (5.7%)	3 (4.1%)	6 (7.7%)
Other	63 (32.8%)	28 (38.4%)	26 (33.3%)
Households’ supervisor education				1.0^b
Primary school & below	88 (45.8%)	33 (45.2%)	34 (43.6%)
Secondary school	92 (47.9%)	34 (46.6%)	39 (50.0%)
Collegiate and above	12 (6.3%)	6 (8.2%)	5 (6.4%)
Household's income level				1.0^b
Low	25 (13.0%)	8 (11.0%)	11 (14.1%)
Medium	125 (65.1%)	48 (65.8%)	47 (60.3%)
High	42 (21.9%)	17 (23.3%)	20 (25.6%)
Food security status				0.17^b
HFS	54 (28.1%)	26 (35.6%)	18 (23.1%)
MFS	50 (26.0%)	20 (27.4%)	26 (33.3%)
LFS	66 (34.4%)	22 (30.1%)	27 (34.6%)
VLFS	22 (11.5%)	5 (6.8%)	7 (9.0%)
Stage of change in food security				0.03 ^b
Pre-contemplation	30 (15.6%)	3 (4.1%)	15 (19.2%)
Contemplation	112 (58.3%)	46 (63.0%)	46 (59.0%)
Decision	39 (20.3%)	19 (26.0%)	14 (17.9%)
Action	4 (2.1%)	3 (4.1%)	0
Maintenance	7 (3.6%)	2 (2.7%)	3 (3.8%)

BMI: body mass index; FM: fat mass; HFS: high food security; TBW: total body water; LFS: low food security; MFS: marginally food security; VLFS: very low food security; WC: waist circumference.

Notes: N refers to the number of respondents.

Symmetric variables—mean ± standard deviation; asymmetric—median. Bold values showed significant P-values.

Independent t test.

Trend chi-square test.

As shown in Table 2, food insecurity was significantly decreased in the intervention group three months after and six months after the intervention. These changes were significant in follow-up time and treatment effect. Although, the interaction between the intervention group and follow-up time in food security was not statistically significant (p = 0.17).

Table 2.

The frequency, percent, and significance level of food security in the intervention and control groups before, immediately, and six months after the intervention.

Variables			Time			p value
Variables			Before the intervention	3 months after the intervention	6 months after the intervention	Follow-up time ^a	Treatment effect ^a	Interaction (time-groups) ^a
Groups	Case	HFS MFS LFSVLFSTotal	26 (35.6)20 (27.4)22 (30.1)5 (6.8)73 (100)	35 (47.9)27 (37.0)8 (11.0)3 (4.1)73 (100)	30 (41.1)34 (46.6)9 (12.3)0 (0.0)73 (100)	0.01*	0.009*	0.17
Groups	Control	HFS MFS LFSVLFSTotal	18 (23.1)26 (33.3)27 (34.6)7 (9.0)78 (100)	19 (24.4)30 (38.5)23 (29.5)6 (7.7)78 (100)	19 (24.4)30 (38.5)22 (28.2)7 (9.0)78 (100)	0.01*	0.009*	0.17

HFS: high food security; LFS: low food security; MFS: marginally food security; VLFS: very low food security.

N (%) is reported.

p values for differences among three trial periods (repeated measures analysis of variance).

*p < 0.05 is significant. Bold values showed significant P-values.

Table 3 shows the anthropometric changes for the intervention group by responder category versus nonintervention comparison group. As a result of the five-week program, after six months follow-up, the intervention group significantly decreased weight (−1.29 kg), BMI (−0.54), and WC (−3.48 cm); in contrast, the comparison group gained a slight amount of weight, BMI, and WC during the intervention period (weight (+1.27 kg), BMI (+0.36) and WC (+0.74 cm)). Although differences between the two groups were not statistically significant except in interaction between intervention groups and follow-up time (Table 3).

Table 3.

The mean, standard deviation, and significance level of the anthropometric indices in the intervention and control groups before, immediately, and six months after the intervention.

		Time			P-value
Variables	Groups	Before the intervention	3 months after the intervention	6 months after the intervention	Follow-up time ^a	Treatment effect ^a	Interaction (Time-groups) ^a
Weight (kg)	CaseControl	73.61 ± 11.6370.81 ± 10.59	72.59 ± 11.4271.23 ± 11.46	72.32 ± 11.2072.08 ± 11.25	0.27	0.42	<0.001*
BMI (kg/m²)	CaseControl	30.57 ± 4.4529.10 ± 4.64	30.14 ± 4.3629.11 ± 4.80	30.03 ± 4.2529.46 ± 4.71	0.07	0.16	<0.001*
WC (cm)	CaseControl	101.22 ± 10.7599.60 ± 10.60	99.65 ± 9.9499.70 ± 10.90	97.74 ± 14.23100.34 ± 10.54	0.07	0.84	0.004*
WHR	CaseControl	0.94 ± 0.060.94 ± 0.05	0.93 ± 0.060.94 ± 0.05	0.91 ± 0.110.94 ± 0.05	0.06	0.40	0.06

BMI: body mass index; WC: waist circumference; WHR: waist hip ratio.

Mean ± SD is reported.

p values for differences among three trial periods (repeated measures analysis of variance).

*p < 0.05 is significant. Bold values showed significant P-values.

Our results also show the mean of FM and TBW decreased in the intervention group and differences between the two groups were statistically significant in follow-up time and interaction between the intervention group and follow-up time (Table 4).

Table 4.

The mean, standard deviation, and significance level of body composition in the intervention and control groups before, immediately, and six months after the intervention.

		Time			P-value
Variables	Groups	Before the Intervention	3 months after the Intervention	6 months after the Intervention	Follow-up Time ^a	Treatment Effect ^a	Interaction (Time-groups) ^a
FM	CaseControl	44.27 ± 5.1442.26 ± 6.10	42.87 ± 5.6942.03 ± 6.16	42.93 ± 5.5443.02 ± 6.27	<0.001*	0.32	<0.001*
TBW	CaseControl	44.30 ± 2.9445.32 ± 3.67	44.19 ± 2.7344.98 ± 3.71	44.53 ± 2.6945.01 ± 3.68	0.01*	0.14	0.005*

FM: fat mass; TBW: total body water.

Mean ± SD is reported.

p values for differences among three trial periods (repeated measures analysis of variance).

*p < 0.05 is significant. Bold values showed significant P-values.

Discussion

The current study is the first to evaluate how nutrition education intervention, in accordance with TTM, affects Iranian women's anthropometry, body composition, and food security. Because behaviors related to individual lifestyles can be complex, using individualized stage-matched multiple education interventions using TTM is a promising approach to managing multifactorial health problems (Rosas et al., 2015). It has been established that people's eating habits have several problems and they do not apply recent recommendations in their lifestyles (Eaton et al., 2012). Individualized TTM-based interventions that change one behavior can help to change another behavior and should be considered a cost-effective strategy for weight management in primary health care when combined with usual care (Menezes et al. 2016).

According to the findings of this study, food insecurity was reduced among the intervention group after the nutrition education intervention. The improvement in participant status in our study from the VLFS to the moderate and HFS is a reasonable change that has its roots in the TTM-based intervention. LFS is defined as “reports of reduced quality, variety, or desirability of diet” and VLFS defined as “Reports of multiple indications of disrupted eating patterns and reduced food intake” is accompanied by hunger (USDA, 2015). In accordance with our study, the results of a multistate study confirm the effects of nutrition education in improving management skills of food resources in individuals of low-income regions (Auld et al., 2015).

In the present study, the mean weight, BMI, and WC decreased in the intervention group at the end of the study. Similar to our findings, other studies also have demonstrated the positive effects of TTM-based interventions on anthropometric indices. These reductions in weight, BMI, and WC are noteworthy since weight loss especially in low-income populations is very challenging. Additionally, according to clinical recommendations from the National Institutes of Health, weight loss programs that incorporate elements of behavioral therapy, physical activity, and diet usually result in weight losses of between 5% and 10% after six months of treatment (NHLBI, 2013). Sanaeinasab et al. also indicated that a psychoeducational intervention for weight management of obese military personnel resulted in weight loss (6.89 kg) in this population (Sanaeinasab et al., 2019). Another randomized controlled trial based on TTM by de Menezes et al. showed a reduction in weight (2.45 kg) in participants (de Menezes et al., 2015). In addition, the results of nutrition and physical activity interventions carried out in mothers of young children living in low-income regions showed a 2.4 kg decrease in weight after a six-month clinical trial (Jordan et al., 2008). However, few studies showed that average weight change even after adjustment for the intentions to change (weight and foods) was not significantly different between the intervention group (−0.77 kg) and the control group (−0.27 kg) (Kjøllesdal et al., 2011). The relationship between the weight loss achieved and the number of group sessions was no longer significant (Kjøllesdal et al., 2011). Although the average weight loss in our study was not significant, at least preventing further weight gain or modest weight loss may have significant public health benefits in a high-risk population. The findings suggest the TTM-based intervention approach is a weight loss behavior for usual public health care and communities of low socioeconomic status.

In this study, the mean of FM and TBW decreased in the intervention group and the differences between the two groups were statistically significant in follow-up time and interaction between the intervention group and follow-up time. These findings were consistent with the results reported by Karintrakul et al. that evaluated the effectiveness of an individualized nutrition counseling program matched with a TTM on overweight and obese females in a randomized controlled trial in Thailand (1.54% decrease in total body FM) (Karintrakul and Angkatavanich, 2017). In the study by An et al., a personalized dietary intervention in overweight and obese Korean adults resulted in a 0.7 g reduction in total body FM (An et al., 2019). Similarly to these reports, Friedrich et al. showed a 2.6% decrease in total body FM and a 2% increase in TBW following pro-health nutrition education confirming current findings (Friedrich and Goluch-Koniuszy, 2015). These achievements demonstrated that TTM-based interventions have a positive effect on body composition.

Adherence to intervention is one of the main determinants of its success influenced by multiple factors such as socioeconomic status, education levels, recognition of risk behaviors, occupation, and the development of self-care (Zanetti et al. 2015). On the other hand, participants saw several health benefits with the TTM-based intervention. TTM-based individualized interventions allow for differentiated interventions based on individual subjective perception.

The limitations and strengths

This study was a randomized clinical trial with a rigorous study design conducted in primary care settings. Although recent literature shows variable effects of interventions after TTM, few studies have been conducted in the context of public health. The extension of interventions in these locations may allow us to extrapolate the measures to population groups and improve the proposed actions by Primary Health Care. In contrast to many studies, all women received the intervention not just those considered “at risk,” which is another positive feature of this intervention. An interdisciplinary team performed the TTM-based intervention that involved nutrition education along with behavior change theories. All subjects in the action and maintenance phase were able to improve their eating habits.

The members of the nonintervention comparison group were exposed to some nutritional interventions that may be viewed as a limitation of the study. However, they received the “usual care” that did not incorporate TTM, which was relatively common in similar studies. Because the intervention was conducted in a public health service, this limitation could not be circumvented. It is noteworthy in this study that the performed activities by the comparison group compared to the intervention group demonstrated similar participation. In addition to proving the efficacy of the interventions by the studies conducted under ideal status, it is necessary to prove the effectiveness of the interventions under routine situations in health services. Thus, we highlighted that there is a new perspective on public health nutrition in the concept of evidence-based public health.

Conclusions and implications

In the present study, the results of six-month TTM-based intervention among women were positive that revealed to be a strategy that may improve anthropometric and nutritional status. Although some previous studies have reported that there is little evidence for sustained weight loss with TTM-based interventions, TTM combined with diet and exercise interventions tends to lead to better outcomes for health (Tuah et al., 2011; Mastellos et al., 2014). Our findings showed a reduction of excess weight and FM as well as an improvement in household food security status. The accomplishments of this study strengthen the body of research supporting the efficiency of TTM-based interventions in achieving desired behavior change under various circumstances. Additionally, it might support the growth of public health initiatives that promote population health. Therefore, government programs that offer nutritional counseling and physical activity without charge should be prioritized to help the subjects to promote consistent changes in physical activity and eating habits.

Footnotes

Acknowledgments

The researchers appreciate the women participated in the study. The ethical committee of Tabriz University of Medical Sciences, Tabriz, Iran, certified the study protocol by reference number: IR.TBZMED.REC.1396.291.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical approval

The study protocol was certified by the ethical committee of Tabriz University of Medical Sciences by reference number: IR.TBZMED.REC.1396.291.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Marziyeh Ebadi-Vanestanagh

Roghayeh Molani-Gol

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