Background:Today, ensuring people’s health and well-being has become a concern for societies. Health status results from an interaction of an individuals’ various psychological, social, and physical aspects.
Objectives:This study aims to investigate the relationship of parental mental health and dietary pattern with adolescent mental health.
Patients and Methods:In this study, 250 high school students in Shiraz were selected using random cluster sampling. The samples were analyzed using the Food Frequency Questionnaire (FFQ) and the General Health Questionnaire (GHQ-28).
Results:According to the findings, parental mental health explains 22% of the variance in children’s mental health, so that in simultaneous regression, physical dimensions, anxiety, social functioning, and depression predicted 13%, 24%, 11%, and 24% of the variance of criterion variables, respectively. No significant relationship was observed between dietary pattern and adolescent mental health dimensions. There was a significant negative relationship only between depression and vegetable intake. Moreover, fruit (r = 0.15, P < 0.05) and vegetable (r = 0.16, P < 0.05) intake had a significant relationship with parental mental health dimensions.
Conclusions:Parents’ mental health and their psychological characteristics can be related to children’s mental health and affect their dietary intake patterns.
Family is considered the first place where mental health is provided. Health during adolescence and adulthood is completely related to family behavior patterns during childhood and adolescence (1). Family health and functioning can also play a significant role in children’s future behavior (2). Studies show that parental psychological symptoms and problems as risk factors are related to externalizing and internalizing problems in children (3, 4). Physical and psychological characteristics, as well as conditions governing family member relationships (such as depression, aggression, and emotional coldness) endangers the physical and psychological health of family members, especially children. Those living in families with high levels of conflict, misbehavior, coldness, and lack of support will suffer poor mental health (5, 6) and face a wide range of physical and mental health problems (7). In a study on children with eating disorders, Bosco et al. (8) found that there was a relationship between parental psychological symptoms and children’s psychological symptoms. Appropriate dietary patterns is another factor that affects well-being and enjoyment of a long healthy life (7). Family environment and parents play a significant role in dietary patterns and eating behaviors (9). Children’s first experiences towards their eating habits and behaviors occur in the family environment, and this behavioral modeling is under the influence of parents (10). In his studies, Bruch and Touraine (11) found that parental, especially maternal, mental disorders (anxiety and depression) are related to high levels of dietary intake. In another study on children with eating disorders, LaPorte and Stunkard (12) found that parents’ understanding and awareness of dietary behaviors are related to the successful treatment of their children. About half of premature deaths under the age of 65 are related to dietary factors (13). Healthy eating, intake of nutrients required for the body, and having a healthy lifestyle are among the factors associated with the outbreak of chronic diseases such as cancer, hypertension, and cardiovascular diseases. Accountability and individual choices play a significant role in creating a healthy lifestyle and dietary pattern during life.
This study aims to investigate mental health and dietary pattern in parents and adolescents.
3. Patients and Methods
The statistical population of this descriptive-correlational study includes all guidance school and high school students of Shiraz and their parents. The study aimed to investigate the relationship of parental mental health and dietary pattern with adolescent mental health. The samples included 250 individuals who were selected using random cluster sampling from the schools in four educational districts in Shiraz. First, five schools out of all existing public schools were selected. Then, two classes out of each school were selected, and all students and their parents were investigated.
3.1. Assessment Tools
In addition to a demographic characteristics checklist, the Food Frequency Questionnaire (FFQ) and the General Health Questionnaire (GHQ-28) were used in this study.
3.2. The Food Frequency Questionnaire (FFQ)
The Food Frequency Questionnaire (FFQ) is generally the most appropriate long-term assessment method. Ease of use, relatively low cost, and comparitvely quick assessment of people’s usual intake have turned this questionnaire into a fully functional tool. Since this questionnaire is the best possible tool to classify people based on their usual food and nutrition intake, accurately measuring intake through the questionnaire is very important (14). This questionnaire consists of 54 food items accross the six major food groups (breads and cereals, dairy products, fruits, vegetables, meats and proteins, and others). Content validity was used to assess the validity of the questionnaire. Before administration, the questionnaire was assessed by some nutrition experts. As previously mentioned, the questionnaire is able to assess family dietary patterns. Chronbach’s alpha was used to assess the reliability of the questionnaire, which included 0.6, 0.43, 0.85, 0.77, 0.32, and 0.82 respectively.
3.3. The General Health Questionnaire (GHQ-28)
The General Health Questionnaire (GHQ-28) was designed by Goldberg and Hillier in 1979 (15). This questionnaire has been translated into 138 different languages, and many studies have been conducted in 70 countries using this questionnaire (16). The questionnaire consists of four subtests, each with seven questions. Questions 1 - 7, 8 - 14, 51 - 21 and 22 - 28 are related to the subtests of physical symptoms, anxiety, social dysfunction, and depression, respectively. Several studies have assessed the validity and reliability of this test. Taghavi (17) calculated the validity of this questionnaire through factor analysis with varimax rotation and presented coefficients between 0.71 and 0.84 for the above-mentioned subscales. The study also assessed the reliability of this test using Chronbach’s alpha and reported that this coefficient was 0.84, 0.71, 0.84 and 0.84 for the subscales of physical symptoms, anxiety, social functioning, and depression, respectively. Given these coefficients and the emphasis on repeated administration of the general health questionnaire in Iranian society, the validity and reliability of the questionnaire has been confirmed.
The samples consisted of male students (33%) and female students (67%). The average age of the students was 15.52 years.
|Mean ± SD||N||Mean ± SD||N||Mean ± SD||N|
|Age, y||15 ± 1.69||66||15. 79 ± 1.43||129||15.52 ± 1.57||195|
|Height||162.41 ± 17.11||46||163.73 ± 5.98||85||163.27 ± 11.17||131|
|Weight||60.46 ± 15.13||48||56.24 ± 9.98||89||57.72 ± 12.15||137|
|BMI||23.86 ± 6.47||45||21.06 ± 3.25||85||22.03 ± 6.26||130|
The results of dietary pattern analysis in the students showed that the highest and lowest intakes belonged to dairy products and vegetables with an average of 2.57 and 2.04, respectively. Simultaneous entry multiple regression analysis was used to assess the relationship between parental mental health and adolescent mental health. Parental mental health and adolescent mental health were analyzed as predictor and criterion variables, respectively. Table 2 shows the results of this analysis.
|Parental mental health||48.0||47.0||47.0||22.0||17.7||0.0001|
Parental mental health has a significant positive relationship with children’s mental health. It explains 22% of the variance in children’s mental health. To assess the relationship between parental mental health and children’s mental health, the results of simultaneous entry multiple regression analysis showed that physical anxiety, social functioning, depression, and general health dimensions predicted 13%, 24%, 11%, 24%, and 23% of the variance of criterion variables, respectively. These results also showed that each parental mental health dimension is related to the same dimension in adolescent mental health. Simultaneous entry multiple regression analysis was also used to assess the relationship between dietary pattern and adolescent mental health. First, dietary pattern and children’s mental health dimensions were analyzed as predictor and criterion variables, respectively. In analyzing the findings in the physical (R = 0.04, R2 = 0.19), anxiety (R = 0.2, R2 = 0.04), and social functioning (R = 0.22, R2 = 0.05) dimensions, no significant relationship was observed between the dimensions of dietary pattern and children’s mental health. Among dietary pattern dimensions, only vegetable intake had a significant negative relationship with adolescent depression (R = 0.27, R2 = 0.07). In other words, increased vegetable intake is accompanied by decreased adolescent depression. On the whole, predictor variables explain 7% of the variance in adolescent depression. The results showed that the two pattern dimensions of fruit (r = 0.15, P < 0.05) and vegetable (r = 0.16, P < 0.05) intake have a significant negative relationship with overall parental mental health. In other words, increased fruit and vegetable intake is accompanied by increased parental mental health.
The results also showed that parental depression has a significant positive relationship with meat intake. In other words, increased parental depression is accompanied by increased meat intake. Predictor variables explain 4% of the variance in this criterion variable (Table 4).
There is no significant relationship between the dimensions of parental mental health and dairy products intake. According to the results shown in Table 4, there is a significant negative relationship between the anxiety and social dysfunction dimensions and fruit intake. In other words, increased fruit intake is accompanied by decreased anxiety and social dysfunction. Predictor variables explain about 7% of the variance in this criterion variable.
The results of simultaneous regression analysis to predict vegetable intake in terms of parental mental health showed that the intake of vegetables (R = 0.21, R2 = 0.04), breads and cereals (R = 0.15, R2 = 0.02), and other foods (R = 0.09, R2 = 0.01) has no significant relationship with the dimensions of parental mental health.
This study aimed to investigate the relationship between parental mental health and dietary pattern of adolescents. Parental mental health, and the mental and emotional atmosphere within families, have a significant relationship with children’s mental health. Studying risk factors shows that parents’ psychological symptoms and problems are related to the externalizing and internalizing of problems in children (3, 4, 7). Stressors resulting from parental psychopathology, family conflicts and disputes, marital discord, and emotional coldness can cause and intensify children’s psychological problems (4, 18). Through environmental impacts, parents increase the risk of similar problems in their children (19). Tension and aggression (20-24), emotional coldness (24), neuroticism (6), marital discord and economic constraints (8, 9), stress, anxiety, and depression (6, 25-27) are among the factors influencing the mental health of family members, especially children. In a study entitled “The relationship between parental psychological problems and characteristics with obesity in adolscents”, Favaro and Santonastaso (6) found that maternal neurotic traits and expressed anxiety through physical (somatic) symptoms were related to some degree to obesity in children. Perceived parent-induced stress by children can be related to nutritional behavior and food pattern (25-27) and intake. This is observed in 30% - 43% of adults and adolescents (26). Sometimes, changes in healthy food intake patterns and high-energy, high-fat, and high-sugar foods can be also considered as an avoidance coping mechanism against stress (28). Johnson et al. (29) also considered family dietary patterns as a coping mechanism against negative emotions in adolescents. Through the increasing of negative mood and feeling of loss of control, stress can also result in diet failure (30). Therefore, a family’s quality and functioning, as well as their psychological health, can be considered an important predictor variable that is related to emotional and behavioral problems in adolescents (31, 32), including poor dietary habits (25, 26), obesity and weight gain (30), risky behaviors and substance abuse (33). In studying family and parent-child pshychodynamics, three states are most highlighted: 1) parenting practices and creating a healthy lifestyle without useless rules, strict regulations, and emotional coldness (22, 24); 2) parental, especially maternal, mental health (6, 11); and 3) children’s problems concerning education and learning, which sometimes includes irritable mood and internal reaction (feeling of anxiety, depressed mood, psychosomatic symptoms) or external reaction (suicidal behavior, aggression, oppositional behavior) (34). In the individual vulnerability model inadequate care, attachment, low self-esteem, and poor social skills are mentioned. According to this model, parental psychopathology and parenting practices are more effective in increasing the risk of eating disorders. Parental feeding practices (35-37) and intake of different types of foods are under the influence of the family (38-41). In addition to modeling food choice, the family creates feeding practices and food acceptance patterns. In the psychopathological model, the first stage is to help patients with eating disorders using cognitive approaches and stopping unhealthy diets. The next stages deal with management, stress control, problem solving, and impulse control techniques in order to increase self-control (30). Therefore, it is necessary to pay attention to psychological factors in treatment programs and eating disorder prevention. Given the limitations of this study, such as retrospective data collection, there might be some errors in recalling past behaviors.
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