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Dietary diversity and mental health in preschoolers in rural China

Published online by Cambridge University Press:  14 December 2020

Shaoping Li
Affiliation:
China Center for Agricultural Policy, School of Advanced Agricultural Sciences, Peking University, Beijing100871, People’s Republic of China
Kevin Chen
Affiliation:
China Academy for Rural Development, Zhejiang University, Hangzhou, Zhejiang Province, People’s Republic of China International Food Policy Research Institute, East and Central Asia Office, Beijing, People’s Republic of China
Chengfang Liu*
Affiliation:
China Center for Agricultural Policy, School of Advanced Agricultural Sciences, Peking University, Beijing100871, People’s Republic of China
Jieying Bi
Affiliation:
Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing, People’s Republic of China
Zhenya He
Affiliation:
Faculty of Business and Economics, The University of Hong Kong, Hong Kong, People’s Republic of China
Renfu Luo
Affiliation:
China Center for Agricultural Policy, School of Advanced Agricultural Sciences, Peking University, Beijing100871, People’s Republic of China
Yanying Yu
Affiliation:
China Academy for Rural Development, Zhejiang University, Hangzhou, Zhejiang Province, People’s Republic of China
Zimeiyi Wang
Affiliation:
International Food Policy Research Institute, East and Central Asia Office, Beijing, People’s Republic of China
*
*Corresponding author: Email cfliu.ccap@pku.edu.cn
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Abstract

Objective:

To investigate the prevalence of mental health problems among preschoolers in rural China and examine the relationship between dietary diversity and mental health.

Design:

A cross-sectional survey analysis was performed. Child mental health was assessed with the Strengths and Difficulties Questionnaire (SDQ). Child dietary diversity was assessed with the dietary diversity score (DDS), which was calculated based on nine food groups using a 24-h recall method. Data were analysed using unadjusted and adjusted logistic regression models.

Setting:

Two nationally designated poverty counties in Hunan Province of China.

Participants:

Preschoolers (n 1334) aged 3–5 years, preschools (n 26).

Results:

Of 950 preschoolers with data on both dietary diversity and mental health, 663 (70 %) were classified as having at least one kind of mental health problem. The prevalences of emotional symptoms, conduct problems, symptoms of hyperactive/inattention, peer relationship problems and poor prosocial behaviour were 39, 27, 23, 12 and 26 %, respectively. Male preschoolers showed higher risks of having mental health problems than their female counterparts on each SDQ subscale except for conduct problems. Moreover, a higher DDS was significantly associated with a lower likelihood of having symptoms of hyperactivity/inattention, peer relationship problems and prosocial behaviour problems after adjustment for confounders (preschoolers’ age, gender, cognitive ability, parental migration status, primary caregiver’s education and household socio-economic status).

Conclusions:

The prevalence of mental health problems was high among preschoolers in rural China. Improving child dietary diversity might be an important strategy to consider in the design of interventions to improve child mental health.

Type
Research paper
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of The Nutrition Society

Mental health problems in adults can originate as early as childhood(Reference Kessler, Angermeyer and Anthony1). It is estimated that, globally, mental health problems affect 10–20 % of children and adolescents(Reference Kieling, Baker-Henningham and Belfer2), and they have been found to have a serious impact on children’s and adolescents’ future life behaviours, such as school dropout, substance abuse, family violence and even suicide(Reference Bao, Jing and Jin3). Beyond the impact on individuals, the economic loss (e.g. human capital loss) resulting from mental disorders also results in enormous disadvantages to societal development(Reference Trautmann, Rehm and Wittchen4). Studies also show that, compared with their urban peers, rural children are more likely to suffer from mental problems(5,Reference Liu, Li and Ge6) . Therefore, effective and efficient interventions to reduce mental health problems in rural children are urgently needed(Reference Fazel, Hoagwood and Stephan7).

Diet has been shown in many studies to be an essential factor that may affect mental health(Reference O’Connell, Boat and Warner8,Reference Jacka, Kremer and Berk9) . In a systematic review, children and adolescents with healthy dietary patterns or consumption of a high-quality diet were found to have lower levels of depression or better mental health(Reference Khalid, Williams and Reynolds10). One study showed that children with high scores for a ‘varied Norwegian’ eating pattern were less likely than those with low scores to have indications of any psychiatric disorders and hyperactivity-inattention disorders(Reference Oellingrath, Svendsen and Hestetun11). The role of the Mediterranean dietary pattern with regard to the prevention of depressive disorders has also been reported(Reference Sánchez-Villegas, Delgado-Rodríguez and Alonso12). Dietary diversity, an integrated indicator for measuring nutrition adequacy and diet quality(Reference Arimond and Ruel13Reference Azadbakht and Esmaillzadeh15), refers to the intake of various food items from different food groups(Reference Azadbakht and Esmaillzadeh15). In the past few years, several studies have identified the association of dietary diversity with anxiety and depressive symptoms among adult women(Reference Poorrezaeian, Siassi and Qorbani16Reference Jiang, Mo and Li18). To the best of our knowledge, however, few studies have examined the relationship between dietary diversity and mental health in children.

The present study aimed to fill the gap mentioned above. To do so, the prevalence of mental health problems among preschoolers in rural China was investigated. Then, the association between dietary diversity and mental health in preschoolers was examined.

Method

The baseline data of a preschool nutrition pilot programme were used, which were collected in September 2018 as part of launched by the government of Xiangxi Prefecture, with support from the World Food Program. The baseline survey was carried out in two nationally designated poverty counties (Longling County and Yongshun County) in Xiangxi Prefecture, Hunan Province, in central-southern China. Because the baseline survey was conducted before any intervention associated with the pilot programme was implemented, the intervention can be ignored here. The sample included twenty-six preschools, which were randomly sampled from fifteen townships across the two project counties. Of these preschools, ten were located in Longling County, and the remaining sixteen were located in Yongsun County. Within each sample preschool, all children aged 3 or 5 years were included in the sample. Primary caregivers of the children (mostly grandparents or parents) were asked in advance to complete the questionnaire and interview in person. A total of 1334 caregivers of preschoolers were surveyed at baseline. In analysis, those preschoolers with missing data for dietary intake, mental health problems or other confounding variables were excluded. In total, 384 caregivers were excluded from the study and 950 (71 %) were included for further analysis.

The mental health of preschoolers was assessed with the parent-reported Mandarin Language Strengths and Difficulties Questionnaire (SDQ)(Reference Goodman19). As a reliable and valid behavioural screening questionnaire(Reference Goodman19Reference Du, Kou and Coghill21), the SDQ has been extensively used by researchers and clinicians in their studies worldwide, such as in Europe(Reference Wiles, Northstone and Emmett22,Reference Kohlboeck, Sausenthaler and Standl23) , the Middle East(Reference Thabet, Stretch and Vostanis24), Australia(Reference Renzaho, Kumanyika and Tucker25), China(Reference Bao, Jing and Jin3) and USA(Reference Deater-Deckard, Wang and Chen26). The questionnaire contains twenty-five items to assess emotions, behaviours and relationships among young children(Reference Goodman19). Specifically, there are five subscales within the SDQ, namely, emotional symptoms, conduct problems, symptoms of hyperactivity/inattention, peer relationship problems and prosocial behaviour. Each subscale includes five items. The score of each subscale ranges from 0 to 10, with higher scores indicating more problems, except for the prosocial behaviour subscale, for which a lower score indicates more problems. Each SDQ subscale was further divided into three categories according to the categories described in an earlier study from China(Reference Du, Kou and Coghill21): ‘normal’, ‘borderline’ and ‘abnormal’. The cut-off values to differentiate the three categories are shown in Table 1. Children with any of the problems listed in the SDQ are categorised in either the ‘borderline’ or ‘abnormal’ group.

Table 1 Cut-offs of the Strengths and Difficulties Questionnaire subscales*

* Adapted from Du et al.(Reference Du, Kou and Coghill21).

According to the Guidelines for Measuring Household and Individual Dietary Diversity provided by the Food and Agriculture Organization of the United Nations(Reference Kennedy, Ballard and Dop27), children’s dietary diversity was assessed with the dietary diversity score (DDS) based on nine food groups. Detailed food group classification and example food items in each group were reported in a previous study(Reference Bi, Liu and Li28). Specifically, trained enumerators used two questionnaires to collect detailed information on dietary intake among children. A 24-h recall method was used in both questionnaires. One questionnaire asked primary caregivers what their children had eaten at home as well as what food they had eaten at restaurants or other shops over the past 24 h. The other questionnaire asked preschool kitchen managers what the children had eaten at the preschools over the past 24 h. As such, detailed information on the food consumption of each child both at home and at preschool over the past 24 h was collected, which allowed us to measure the children’s total dietary consumption within the past 24 h. The DDS was calculated by counting the number of food groups that a child had consumed in the past 24 h without consideration of a minimum quantity requirement for any food group. Each individual food item in each food group consumed by a child earned one point for the child’s DDS, but different individual food items consumed in the same group were not counted repeatedly. Therefore, the DDS ranged from 0 to 9.

Information on factors that might potentially confound the relationship between DDS and mental health was also collected in the questionnaire by trained enumerators. In the examination of the associations, the following factors were adjusted: children’s age, gender, left-behind status, BMI, time spent on TV/mobile (<60 min v. >60 min), parental education level (junior high school or below v. senior high school or above), primary caregiver’s education level (junior high school or below v. senior high school or above) and household socio-economic status (SES). Considering that measuring SES in poor settings can be difficult and inaccurate due to income instability or reporting bias(Reference Morseth, Grewal and Kaasa29), the possession of durable goods from a list of thirteen items was recorded to represent the SES of each household. Household SES was divided into three categories: lowest tertile, middle tertile and highest tertile. Moreover, child cognitive function was measured using two indexes from the Wechsler Preschool and Primary Scale of Intelligence, Fourth Edition: working memory index and verbal comprehension index. Both the working memory index and verbal comprehension index were categorised into ‘normal’, ‘borderline’ and ‘abnormal’.

Statistical methods

Wald tests were used to test differences between male and female preschoolers in all measured correlates. Logistic regression models were used to estimate odds, with 95 % CI, of the prevalence of mental health problems across the socio-demographic subgroups (DDS, age, gender, ethnicity, BMI for age z-score, cognitive function, time spent on TV/mobile, parental education level, left-behind status, primary caregiver’s education level and household SES). Adjusted logistic regression models were used to the estimate odds, with 95 % CI, of the prevalence of mental health problems across the sociodemographic subgroups that were significant in the unadjusted logistic regression models. Significance levels were set at a two-tailed P-value ≤0·05 for all tests. All analyses were performed using Stata/se 15.1 (Stata Corporation).

Results

No statistically significant difference in DDS, SDQ score or other confounders (preschoolers’ age, gender, cognitive ability, parental migration status, primary caregiver’s education or household SES) between children who were included in the present analysis and those who were excluded was found. Our main analytical sample included 950 preschoolers for analysis and there were slightly more males (50·4 %) than females (49·6 %) (see Table 2). The mean ages of the male and female participants were 4·02 (1·00) and 4·15 (0·99) years, respectively. There were no significant gender differences found in this study for age, BMI for age z-score, cognitive test performance, time spent on TV/mobile, left-behind status, parental or primary caregivers’ education and household SES. The mean DDS for boys and girls were 5·79 (sd 1·20) and 5·81 (sd 1·27), respectively, indicating that there was no significant difference in the intrahousehold food allocation between boys and girls. A total of 663 (70 %) children in our sample had at least one mental health problem. The prevalence of mental health problems in the overall sample population was 39 % for emotional symptoms, 12 % for peer relationship problems, 23 % for symptoms of hyperactive/inattention, 27 % for conduct problems and 26 % for poor prosocial behaviour. Our study results indicated that boys were more likely than girls to have emotional problems, symptoms of hyperactivity/inattention and peer relationship problems and less likely to show prosocial behaviour.

Table 2 Characteristics of the study participants by gender (n 950)*

WMI, working memory index; VCI, verbal comprehension index; SES, socio-economic status.

* Sample with complete data on both diet and mental health problems. A total of 1334 caregivers of preschoolers were surveyed at baseline. Those preschoolers with missing data for dietary intake, mental health problems or other confounding variables were excluded. In total, 384 caregivers were excluded from the study and 950 (71 %) were included for further analysis.

In the univariable analyses (see Table 3), 5-year-olds were less likely to have any of the problems listed in the SDQ subscales than younger children. Female gender was associated with a lower likelihood of conduct problems and symptoms of hyperactivity/inattention and a higher likelihood of prosocial behaviour. In addition, those who had poor performance on the working memory index and verbal comprehension index had a higher possibility for the presence of mental health problems than those who performed well. Moreover, left-behind children were more likely to have emotional symptoms than those who were taken care of by both parents at home, but they had fewer conduct problems than non-left-behind children. The results also revealed that children whose primary caregivers had higher education levels tended to be less likely to have emotional symptoms. Interestingly, the results indicated that children from households in the highest SES tertile were more likely to have peer relationship problems than those from households in lower SES tertiles.

Table 3 Dietary diversity and sociodemographic characteristics: association with mental health problems*

WMI, working memory index; VCI, verbal comprehension index; SES, socio-economic status.

Bold values represent they are statistically significant.

* Adjusted means for sociodemographic variables that were significant in the unadjusted logistic regression models.

The univariable analysis showed significant differences in dietary diversity based on the presence or absence of mental problems, except for emotional problems and conduct problems (see Table 3). In the unadjusted analysis, children with medium and high DDS were less likely to have symptoms of hyperactivity/inattention than children with low DDS. Similarly, children with high DDS were also less likely to have peer relationship problems and prosocial behaviour problems than children with low DDS.

Adjusting for additional confounding variables did not alter our findings. The association between DDS and mental health problems was similar in the unadjusted model and adjusted model (see Table 3). However, the associations of mental health problems with left-behind status were no longer statistically significant in the adjusted model.

Discussion

The mean DDS for a sample of preschoolers in rural China was 5·80 (sd 1·23), which is relatively low compared with the results from other studies among Chinese children(Reference Meng, Wang and Li30,Reference Jiang, Zhao and Zhao31) . The prevalence of mental health problems was 70 % among these children, which is much higher than previous estimates in China(Reference Qu, Jiang and Zhang32) and other countries(Reference Kovess-Masfety, Husky and Keyes33,Reference Kashala, Elgen and Sommerfelt34) . DDS was significantly associated with several mental health problems, including symptoms of hyperactivity/inattention, peer relationship problems and poor prosocial behaviour, after adjustment for confounders.

A potential reason why the mean DDS in this study was lower than that in previous studies is the higher cost and limited accessibility of a diverse diet(Reference Liu, Shively and Binkley35) given the geographical disadvantages of our sampling areas. Similarly, given the poor access to social and educational facilities in the sample areas, the high prevalence of mental health problems among the sample children might be explained by their exposure to negative environmental stress(Reference Elberling, Linneberg and Olsen36). Older children had a lower risk of each SDQ subscale problem than their younger peers, which was consistent with the results of a study showing that younger children had a higher prevalence of psychological and behavioural problems than older children(Reference Hu, Lu and Huang37). A potential reason for the age difference might be that younger children are not as good as older children in dealing with such problems(Reference Hu, Lu and Huang37). Child cognitive ability was found to be negatively associated with the risks of mental health problems, which is similar to the finding that having a cognitive delay may place children at risk of having behaviour problems(Reference Cheng, Palta and Kotelchuck38). Other socio-economic risk factors for mental health problems among the study population included left-behind status, primary caregiver education and household SES. Children who had at least one parent who had emigrated were at high risk of having emotional symptoms and conduct problems. The findings from a similar Chinese study showed that left-behind children had more symptoms of hyperactivity and less prosocial behaviour(Reference Fan, Su and Gill39). It is not clear why left-behind status has an impact on different mental health problems in these studies, but the risk of having any kind of mental health problem may vary for children exposed to distinct environmental stressors.

The presence of mental health problems was higher among boys than girls, which is consistent with a study in Sichuan, China(Reference Qu, Jiang and Zhang32), and studies among children at similar ages but from other cultures(Reference Liu, Shively and Binkley35,Reference Elberling, Linneberg and Olsen36) . Male preschoolers were shown to be more vulnerable to emotional symptoms, symptoms of hyperactivity/inattention, peer relationship problems and poor prosocial behaviour, which is partially consistent with studies showing that boys have a higher risk of having conduct problems and symptoms of hyperactivity/inattention(Reference Liu, Shively and Binkley35,Reference Elberling, Linneberg and Olsen36) . However, the results from a previous study showed no indications of gender differences at preschool age(Reference Campbell40), which contradicted our findings.

Recent studies have mainly focused on the relationship between dietary patterns or quality and mental health problems(Reference Wiles, Northstone and Emmett22,Reference Kohlboeck, Sausenthaler and Standl23) . For example, a British study linked an unhealthy dietary pattern (e.g. junk food consumption) with hyperactivity among children(Reference Wiles, Northstone and Emmett22). Another Germany study indicated that higher diet quality was related to fewer emotional symptoms and symptoms of hyperactivity/inattention(Reference Kohlboeck, Sausenthaler and Standl23). These findings all provide evidence that dietary diversity, as a key element of a healthy diet and a proxy of diet quality, has an independent impact on mental health. Regarding the association between DDS and mental health problems, there are many potential biological mechanisms by which a varied diet promotes mental health in children(Reference O’Neil, Quirk and Housden41). First, dietary diversity may reflect diet quality and nutritional adequacy among children(Reference Hatløy, Torheim and Oshaug42), which have been linked with mental health issues. For example, the intake of multiple nutrients, such as Zn, folate and Mg, is related to fewer depressive disorders(Reference Jacka, Maes and Pasco43). Second, a poor diet may negatively impact human biological functioning, including oxidative processes, immune response and levels of salient brain proteins, all of which might elicit mental health problems(Reference Hatløy, Torheim and Oshaug42).

This study makes a notable contribution. To the best of our knowledge, this study is the first to examine the relationship between dietary diversity and child mental health. Existing studies have paid much attention to the role of diet quality or a healthy diet in promoting mental health, while few studies have focused on the role of dietary diversity. This study provided evidence that a varied diet is related to a lower likelihood of symptoms of hyperactivity/inattention, peer relationship problems and prosocial behaviour problems among young children and thus is very likely to be taken into account for designing interventions.

However, our study has several limitations. First, the causal relationship between the DDS and mental health could not be determined because of the cross-sectional design. Since children with behavioural problems tend to consume less varied diets, especially diets with fewer servings of fruits and vegetables(Reference Renzaho, Kumanyika and Tucker25), the possibility of reverse causality cannot be excluded. Second, information about some potential confounders, such as child physical activity, total energy intake, household food security and family financial stress, was not obtained due to data unavailability or difficulty for measurement. Therefore, the relationship between DDS and mental health problems in the present study might have been driven by these confounding effects.

Conclusion

The prevalence of mental health problems was relatively high in this study. More attention should be paid to rural, poor areas where children are more likely to have mental illness. Improving child dietary diversity might be an important strategy to consider in the design of interventions to improve child mental health in poor rural areas. The possible causal effect of dietary diversity on child mental health and the mechanism involved should be examined in future prospective studies.

Acknowledgements

Acknowledgements: The authors would like to thank to the staff of the World Food Program China Office at the time the study was performed, especially Mr. Sixi Qu, Ms. Caroline Legros, Ms. Han Jiang and Ms. Jingyi Liu for their role in mobilising the preschool nutrition programme and facilitating the data collection process. Financial support: This research was supported by the National Natural Science Foundation of China (grant nos. 71861147003 and 71925009), the IFPRI Research Project (no. 602174.002.001) funded by the World Food Programme and the China Postdoctoral Science Foundation (grant no. 2019M650361). Conflict of interest: The authors declare that there are no conflicts of interest. Authorship: K.C., C.L., J.B. and R.L. designed the research. S.L. analysed the data and drafted the paper with contributions from Z.H., C.L., Y.Y. and Z.W. All the authors read and approved the final manuscript. Ethics of human subject participation: This study was conducted according to the guidelines laid down in the Declaration of Helsinki, and all procedures involving research study participants were approved by the International Food Policy Research Institute Institutional Review Board (IRB) (DSG-18-0837). Written informed consent was obtained from all legal guardians of children and school staff involved in the study.

References

Kessler, RC, Angermeyer, M, Anthony, JC et al. (2007) Lifetime prevalence and age-of-onset distributions of mental disorders in the World Health Organization’s World Mental Health Survey Initiative. World Psychiatry 6, 168176.Google ScholarPubMed
Kieling, C, Baker-Henningham, H, Belfer, M et al. (2011) Child and adolescent mental health worldwide: evidence for action. Lancet 378, 15151525.CrossRefGoogle ScholarPubMed
Bao, P, Jing, J, Jin, Y et al. (2016) Trajectories and the influencing factors of behavior problems in preschool children: a longitudinal study in Guangzhou, China. BMC Psychiatry. Published online: 01 June 2016. doi: 10.1186/s12888-016-0864-z.CrossRefGoogle Scholar
Trautmann, S, Rehm, J & Wittchen, H (2016) The economic costs of mental disorders. EMBO Rep 17, 12451249.CrossRefGoogle Scholar
U.S. Department of Health and Human Services, Health Resources and Services Administration & Maternal and Child Health Bureau (2011) The Health and Well-Being of Children in Rural Areas: A Portrait of the Nation 2007. Rockville, Maryland.Google Scholar
Liu, Z, Li, X & Ge, X (2009) Left too early: the effects of age at separation from parents on Chinese rural children’s symptoms of anxiety and depression. Am J Public Health 99, 20492054.CrossRefGoogle ScholarPubMed
Fazel, M, Hoagwood, K, Stephan, S et al. (2014) Mental health interventions in schools in high-income countries. Lancet 1, 377387.Google ScholarPubMed
O’Connell, ME, Boat, T & Warner, KE (2009) Preventing Mental, Emotional, and Behavioral Disorders Among Young People: Progress and Possibilities, Vol. 7. Washington, DC: National Academies Press.Google Scholar
Jacka, FN, Kremer, PJ, Berk, M et al. (2011) A prospective study of diet quality, mental health in adolescents. PLoS ONE. Published online: 21 September 2011. doi: 10.1186/s12888-016-0864-z.CrossRefGoogle Scholar
Khalid, S, Williams, CM & Reynolds, SA (2016) Is there an association between diet and depression in children and adolescents? A systematic review. Br J Nutr 116, 20972108.CrossRefGoogle ScholarPubMed
Oellingrath, IM, Svendsen, MV & Hestetun, I (2014) Eating patterns and mental health problems in early adolescence – a cross-sectional study of 12–13-year-old Norwegian schoolchildren. Public Health Nutr 17, 25542562.CrossRefGoogle ScholarPubMed
Sánchez-Villegas, A, Delgado-Rodríguez, M, Alonso, A et al. (2009) Association of the Mediterranean dietary pattern with the incidence of depression: the Seguimiento Universidad de Navarra/University of Navarra follow-up (SUN) cohort. Arch Gen Psychiatry 66, 10901098.CrossRefGoogle Scholar
Arimond, M & Ruel, MT (2004) Dietary diversity is associated with child nutritional status: evidence from 11 demographic and health surveys. J Nutr 134, 25792585.CrossRefGoogle ScholarPubMed
Hatløy, A, Torheim, LE & Oshaug, A (1998) Food variety – a good indicator of nutritional adequacy of the diet? A case study from an urban area in Mali, West Africa. Eur J Clin Nutr 52, 891898.CrossRefGoogle Scholar
Azadbakht, L & Esmaillzadeh, A (2011) Dietary diversity score is related to obesity and abdominal adiposity among Iranian female youth. Public Health Nutr 14, 6269.CrossRefGoogle ScholarPubMed
Poorrezaeian, M, Siassi, F, Qorbani, M et al. (2015) Association of dietary diversity score with anxiety in women. Psychiatry Res 230, 622627.CrossRefGoogle ScholarPubMed
Poorrezaeian, M, Siassi, F, Milajerdi, A et al. (2017) Depression is related to dietary diversity score in women: a cross-sectional study from a developing country. Arch Gen Psychiatry. Published online: 16 November 2017. doi: 10.1186/s12991-017-0162-2.CrossRefGoogle Scholar
Jiang, W, Mo, M, Li, M et al. (2018) The relationship of dietary diversity score with depression and anxiety among prenatal and post-partum women. J Obstet Gynaecol Res 44, 19291936.Google ScholarPubMed
Goodman, R (1997) The strengths and difficulties questionnaire: a research note. J Child Psychol Psychiatry 38, 581586.CrossRefGoogle ScholarPubMed
Goodman, R (2001) Psychometric properties of the strengths and difficulties questionnaire. J Am Acad Child Adolesc Psychiatry 40, 13371345.CrossRefGoogle ScholarPubMed
Du, Y, Kou, J & Coghill, D (2008) The validity, reliability and normative scores of the parent, teacher and self report versions of the Strengths and Difficulties Questionnaire in China. Child Adolesc Psychiatry Ment Health. Published online: 29 April 2008. doi: 10.1186/1753-2000-2-8.CrossRefGoogle Scholar
Wiles, NJ, Northstone, K, Emmett, P et al. (2007) ‘Junk food’ diet and childhood behavioural problems: results from the ALSPAC cohort. Eur J Clin Nutr 63, 491498.CrossRefGoogle ScholarPubMed
Kohlboeck, G, Sausenthaler, S, Standl, M et al. (2012) Food intake, diet quality and behavioral problems in children: results from the GINI-plus/LISA-plus studies. Ann Nutr Metab 60, 247256.CrossRefGoogle ScholarPubMed
Thabet, A, Stretch, D & Vostanis, P (2000) Child mental health problems in arab children: application of the strengths and difficulties questionnaire. Int J Soc Psychiatry 46, 266280.CrossRefGoogle ScholarPubMed
Renzaho, AM, Kumanyika, S & Tucker, KL (2010) Family functioning, parental psychological distress, child behavioural problems, socio-economic disadvantage and fruit and vegetable consumption among 4-12 year-old Victorians, Australia. Health Promot Int 26, 263275.CrossRefGoogle ScholarPubMed
Deater-Deckard, K, Wang, Z, Chen, N et al. (2012) Maternal executive function, harsh parenting, and child conduct problems. J Child Psychol Psychiatry 53, 10841091.CrossRefGoogle ScholarPubMed
Kennedy, G, Ballard, T & Dop, MC (2013) Guidelines for Measuring Household and Individual Dietary Diversity. Rome: Food and Agriculture Organization of the United Nation.Google Scholar
Bi, J, Liu, C, Li, S et al. (2019) Dietary diversity among preschoolers: a cross-sectional study in poor, rural, and ethnic minority areas of Central South China. Nutrients. Published online: 6 March 2019. doi: 10.3390/nu11030558.CrossRefGoogle Scholar
Morseth, MS, Grewal, NK, Kaasa, IS et al. (2017) Dietary diversity is related to socioeconomic status among adult Saharawi refugees living in Algeria. BMC Public Health. Published online: 03 July 2017. doi: 10.1186/s12889-017-4527-x.Google Scholar
Meng, L, Wang, Y, Li, T et al. (2018) Dietary diversity, food variety in Chinese children aged 3–17 years: are they negatively associated with dietary micronutrient inadequacy? Nutrients. Published online: 5 November 2018. doi: 10.3390/nu10111674.CrossRefGoogle Scholar
Jiang, H, Zhao, A, Zhao, W et al. (2018) Do Chinese preschool children eat a sufficiently diverse diet? A cross-sectional study in China. Nutrients. Published online: 20 June 2018. doi: 10.3390/nu10060794.CrossRefGoogle Scholar
Qu, Y, Jiang, H, Zhang, N et al. (2015) Prevalence of mental disorders in 6–16-year-old students in Sichuan Province, China. Int J Environ Res Public Health 12, 50905107.CrossRefGoogle ScholarPubMed
Kovess-Masfety, V, Husky, MM, Keyes, K et al. (2016) Comparing the prevalence of mental health problems in children 6–11 across Europe. Soc Psychiatry Psychiatr Epidemiol 51, 10931103.Google ScholarPubMed
Kashala, E, Elgen, I, Sommerfelt, K et al. (2005) Teacher ratings of mental health among school children in Kinshasa, Democratic Republic of Congo. Eur Child Adolesc Psychiatry 14, 208215.CrossRefGoogle Scholar
Liu, J, Shively, GE & Binkley, JK (2014) Access to variety contributes to dietary diversity in China. Food Policy 49, 323331.CrossRefGoogle Scholar
Elberling, H, Linneberg, A, Olsen, EM et al. (2010) The prevalence of SDQ-measured mental health problems at age 5–7 years and identification of predictors from birth to preschool age in a Danish birth cohort: the Copenhagen Child Cohort 2000. Eur Child Adolesc Psychiatry 19, 725735.CrossRefGoogle Scholar
Hu, H, Lu, S & Huang, C (2014) The psychological and behavioral outcomes of migrant and left-behind children in China. Child Youth Serv Rev 46, 110.CrossRefGoogle Scholar
Cheng, E, Palta, M, Kotelchuck, M et al. (2014) Cognitive delay and behavior problems prior to school age. Pediatrics 134, e749e757.CrossRefGoogle ScholarPubMed
Fan, F, Su, L, Gill, MK et al. (2009) Emotional and behavioral problems of Chinese left-behind children: a preliminary study. Soc Psychiatry Psychiatr Epidemol 45, 655664.CrossRefGoogle ScholarPubMed
Campbell, SB (1995) Behavior problems in preschool children: a review of recent research. J Child Psychol Psychiatry 36, 113149.CrossRefGoogle ScholarPubMed
O’Neil, A, Quirk, SE, Housden, S et al. (2014) Relationship between diet, mental health in children, adolescents: a systematic review. Am J Public Health. Published Online: 10 September 2014. doi: 10.2105/ajph.2014.302110.CrossRefGoogle Scholar
Hatløy, A, Torheim, L & Oshaug, A (1998) Food variety – a good indicator of nutritional adequacy of the diet? A case study from an urban area in Mali, West Africa. Eur J Clin Nutr 52, 891898.CrossRefGoogle Scholar
Jacka, FN, Maes, M, Pasco, JA et al. (2012) Nutrient intakes and the common mental disorders in women. J Affect Disorders 141, 7985.Google ScholarPubMed
Figure 0

Table 1 Cut-offs of the Strengths and Difficulties Questionnaire subscales*

Figure 1

Table 2 Characteristics of the study participants by gender (n 950)*

Figure 2

Table 3 Dietary diversity and sociodemographic characteristics: association with mental health problems*