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Iranian Journal of Child Neurology logoLink to Iranian Journal of Child Neurology
. 2017 Spring;11(2):13–25.

Socioeconomic Status Index to Interpret Inequalities in Child Development

Mahbobeh AHMADI DOULABI 1, Firoozeh SAJEDI 2, Roshanak VAMEGHI 2, Mohammad Ali MAZAHERI 3, Alireza AKBARZADEH BAGHBAN 4
PMCID: PMC5493825  PMID: 28698723

Abstract

Objective

There have been contradictory findings on the relationship between Socioeconomic Status (SES) and child development although SES is associated with child development outcomes. The present study intended to define the relationship between SES and child development in Tehran kindergartens, Iran.

Materials & Methods

This cross-sectional survey studied 1036 children aged 36-60 month, in different kindergartens in Tehran City, Iran, in 2014-2015.

The principal factor analysis (PFA) model was employed to construct SES indices. The constructed SES variable was employed as an independent variable in logistic regression model to evaluate its role in developmental delay as a dependent variable.

Results

The relationship between SES and developmental delay was significant at P=0.003. SES proved to have a significant (P<0.05) impact on developmental delay, both as an independent variable and after controlling risk factors.

Conclusion

There should be more emphasis on developmental monitoring and appropriate intervention programs for children to give them higher chance of having a more productive life.

Introduction

Socioeconomic Status (SES), as a major risk factor, has gained the attention of politicians, managers and researchers throughout the healthcare system (1). SES has been studied from three perspectives: the initial exposure, a risk factor health outcome, and a confounding factor (2). Numerous studies have confirmed SES to be a predictor of child development. Different data support the relationship between SES and child development (3-5).

Children, the most important national focus of each society, determine the future of their society; therefore, their childhood development is an essential component to maintaining health throughout their life (6, 7).

Child development is a process in which brain and nervous system undergo integrated changes due to structural and functional complexity. Subsequently, children acquire new skills and capacity, their compatibility increases and they reach behavioral and functional maturation. Development consists of several domains defined by acquiring specific skills which child gradually learns at their appropriate age (8-12), included physical, social, emotional, cognitive and language domains (13).

The brain growth and development during the early years after birth is rapid and these years are an opportunity for the brain to grow, develop and achieve optimal development, hence, the brain becomes susceptible to negative environmental factors (6, 14, 15). Thus, any impairment in child development can affect child’s health as well as the societies at a larger scale. Investing in child development programs would reduce the cost and burden of chronic diseases and disabilities. Such investment would also improve SES of the society by turning a child into a healthy productive adult and it will compensate several times more than the cost in time (7, 14, 16).

Over 200 million under-five children might never reach full potential of self-cognitive development due to poverty, precarious health, nutrition and lack of environmental stimulation (17). Children suffering from poverty would also face risks of environmental and biological factors, which have accumulative and dynamic impacts on neuro psychomotor development (3, 18-23).

Speech disorders, learning disabilities and emotional disorders are reported in 15-18% of children in different societies. There are also severe psychosocial complications in 15% of the children (24-28) which might also rise up to 30% in at risk children. The prevalence rate of developmental delay in Iranian children ranges from 7% to 26.3% in different cities (29-33).

A meta-analysis study showed 14.6% cumulative frequency in different dimensions of developmental delay in Iranian children (34). Eight percent of children suffer from one or more developmental disorders from birth to 6 yr of age (35).

Average percentage of children delayed in the communication, gross motor, fine motor, problemsolving and social-personal domains was 3.87%, 4.04%, 4.31%, 4.15% and 3.69%, respectively (36).

Children, especially younger ones, are more susceptible to SES and poverty as these two factors would increase the risk of complications such as mental health disorders in children (37). In addition, poverty and low SES are reported to be associated with higher risk of mental health problems (38). Children with low SES also lack access to cognitive experiences and stimulations since having access to these cultural materials acts as a mediator between family income and children’s intellectual growth, academic achievement, as well as behavioral problems (3).

Lower family SES causes higher incidence of developmental delay in children. Low SES would increase unhealthy behaviors, inadequate nutrition, and failure to properly use health care, maternal diseases and drug abuse, and consequently, increase developmental delays (4, 39-41). Mother’s lower levels of education, low income and poor housing conditions are significantly correlated with child’s developmental delay (42). Poverty increases child’s exposure to biological and psychological risk factors, lead to developmental disorders by changing the brain structure and functioning (20). Children living below the poverty line are 1.3 times more prone to suffer from developmental delays or learning disabilities in comparison with non-poor children (43). Poverty can also deeply affect cognitive development and longterm poverty might lead to significant damage in this regard (44). Insufficient family income means lack of financial resources, besides being a stressor for parents and preventing provision of care for their child (45). Stress, anxiety and depression in parents, especially mothers, are associated with developmental disorders in children (46). Furthermore, children living in poverty are more exposed to family conflicts, violence, separation, instability and chaotic family. These children also experience less social support (47).

Few studies have been conducted on the association between SES and child development in Iran and have considered few factors to evaluate SES (31, 32). Therefore, the present research studied SES as an independent variable on child development using the principal component analysis of data provided by studying children aged 36-60 months of age in Tehran, Iran.

Materials & Methods

This cross-sectional descriptive study was conducted from Apr 2014 to Feb 2015 in kindergartens across Tehran, Iran.

The present research studied 1036 paired-samples (parent-child) through a multistage sampling technique.

The samples were all Iranian and children aged 36 to 60 months, living with both parents, and had no recognized developmental disorders due to genetic syndrome, etc.

Simple random sampling technique was employed to choose 43 kindergartens out of all kindergartens in Tehran (North, South and Center), children (and their parents) who met the inclusion criteria were recruited.

The data collection instruments included parents-child demographic inventory, socioeconomic questionnaire.

The demographic inventory included parents’ general information (age, educational attainment, job, gravidity and parity, and history of abortion). The socioeconomic status was assessed by studying income, price square feet residential ground, infra-structure, hosing, number of family, parental education, number of cars, and personal computer The reliability of the demographic questionnaire was evaluated through content validity using scientific resources and experts’ opinion. The validity and reliability of the demographic, socioeconomic status, and child specification questionnaire were determined using content validity and test-retest. (The correlation coefficient was 93-97% from 10 checklists).

ASQ is currently the most widely used. Sensitivity of the ASQ test is 75% in high risk group and 100% in the community group, with specificity of 95% and 90%, respectively (48) .Validity of this test varies from 76% to 88%. In addition, ASQ includes 19 different questionnaires that can screen developmental status of children from 4 to 60 months in five different domains: communication, gross motor, fine motor, problem solving and personal-social skills. Each domain is evaluated by six questions on what the child can or cannot do. They are selected to be representatives of a developmental quotient of 75-100%. The answer of parents to each question is “yes” to indicate that the child does the special behavior of this item, ‘sometimes’’ to indicate an occasional or emerging response and ‘‘not yet’’ to indicate that their child does not yet do the behavior, with a respective score of 10, 5 or 0 points.

Then, scores of each item summed and final score in each domain is compared to cut-off points of the ASQ guidelines. The score on any domain below the cut-off point or higher than two standard deviations below the mean of the reference group, is considered abnormal and referral for further evaluation (49-53).

ASQ is a reliable tool with Cronbach’s alpha of 0.86 and reliability of 0.93 for Iranian children (54). The reliability of this scale in present study was obtained as 0.88, using the test-retest method.

The researcher got required permissions to conduct the study and obtained written informed consents from kindergarten teachers after introducing the objectives and asking for their cooperation. The mother/child Demographic Questionnaire, Socioeconomic Survey Questionnaire, and the age-appropriate Ages and Stages Questionnaire (ASQ) were given to mothers to be filled out at home (within four days). The researcher calculated the scores in ASQ based on age-appropriate cut off values. Mothers were informed of the results and they were referred to responsible organizations if the score was below the cutoff value.

The principal component analysis (PCA) was used to create SES variable. PCA is a multivariate statistical method widely used during recent years to build SES variable in studies related to health and SES (55-60). We studied the impact of family’s SES on child development and employed PFA model to create an index of family SES and create an overall SES variable from combination of related variables.

The family SES index was evaluated using the following variables: parent’s education, household ownership, floor area of the housing unit, family property such as having one or two cars, household monthly income, having a computer, number of family members. PFA variable was an overall score and considering the qualitative nature of some variables in PCA, polychoric correlation matrix was used and an SES variable was created based on factor loadings. Then this score was categorized into five levels as follows: very low, low, moderate, high and very high, Logistic regression model was used to evaluate its relationship as an independent variable, as well as with controlling main underlying risk factors, to predict odds ratio of developmental delay with two codes, 0 and 1, as the outcome variables.

The data were analyzed using SPSS ver. 16 (Chicago, IL, USA) and Stata ver. 13. Mann Whitney test and logistic regression models were employed at significance level of 0.05.

All research ethical considerations were taken into account. The Ethics Committee of the University of Welfare and Rehabilitation Sciences confirmed the study. The participants were completely informed of the procedures and their informed written consents were obtained during data collection.

Results

Family SES: PFA model was used to create an overall SES index and variables mentioned above were entered into the model. The first component had greater proportion in explaining variances in SES so that it explained about 75% of the total variance (Eigenvalue of 3.36). Table 1 presents the eigenvector corresponding to this component for different SES variables. The variables of “no personal computer” and “no car” had higher weight in comparison with other variables in the first principal component.

Table 1.

Eigenvectors Components (Regression Ranking Coefficients

Variables Eigenvectors
for first element 		The portion of the total
variance 		Eigen value
Maternal ’s education 0.168772 0.7543 3.36408
Paternal’ s education 0.08268
Income 0.12104
Infrastructure 0.07021
residential land price(M2) 0.13745
no personal computer -0.28647
No car 1 -0.29761
No car 2 -0.8786
Number of family members -0.5682
Hosing -0.3338
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A general score was determined for SES according to predict proxy and this score was divided into five levels (very low to very high or 1 to 5, respectively) and based on percentiles 40, 20, 60, 80.

The prevalence of developmental delay of the sample was 16.2% and there was a significant difference between different family SES levels at P=0.003, using Mann-Whitney U-test such that a decrease in SES resulted in an increase in the prevalence of developmental disorders (Table 2). Table 3 presents the developmental status in five dimensions with various levels of SES.

Table 2.

Frequency of Developmental Delay in Children Aged 36-60 Months

Domains Normal Development
Frequency(percent) 		Delay Development
Frequency(percent) 		Total
LEVEL1 155(74.5 ) 53(25.5 ) 208 (100.0 )
LEVEL2 176(85.0 ) 31(15.0 ) 207 (100.0 )
LEVEL3 181(87.4 ) 26(12.6 ) 207(100.0 )
LEVEL4 179(86.1 ) 29 (13.9 ) 208(100.0 )
LEVEL5 177(85.9 ) 29(14.1 ) 206(100.0 )
TOTAL 868(83.8 ) 168(16.2 ) 1036(100.0 )
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Result of Mann-Whitney U P=0.003

Table 3.

Relation of Socio -Economic Status and Developmental Delay with 5 Domains of Development

Domains Communication Fine Motor Gross Motor Problem-
Solving 		Personal
social
Delay
(+) 		Delay
(-) 		Delay
(+) 		Delay
(-) 		Delay
(+) 		Delay
(-) 		Delay
(+) 		Delay
(-) 		Dela
(+) 		Delay
(-)
LEVEL1 27
(13.0%) 		181 (87.0%) 15
( 7.2% ) 		193
(92.8 %) 		18
(8.7% ) 		190
( 91.3% ) 		18
(8/7%) 		190
(91.3%) 		14
(6.7%) 		194
(93.3%)
LEVEL2 21
(10.1%) 		186
(89.9%) 		8
( 3.9% ) 		199
( 96.1% ) 		10
( 4.8% ) 		197
(95.2%) 		7
( 3.4% ) 		200
( 96.6%) 		5
(2.4%) 		202
(97.6%)
LEVEL3 7
(3.4%) 		200
(96.6%) 		8
( 3.9% ) 		199
(96.1 %) 		11
(5.3% ) 		196
(94.7% ) 		7
( 3.4% ) 		200
( 96.6% ) 		7
(3.4%) 		200
(96.6%)
LEVEL4 9
(4.3% ) 		199
(95.7%) 		14
( 6.7% ) 		194
( 93.3% ) 		9
(4.3% ) 		199
(95.7%) 		9
( 4.3% ) 		199
(95.7% ) 		4
(1.9%) 		204
(98.1%)
LEVEL5 8
(3.9%) 		198
(96.1%) 		13
( 6.3% ) 		193
(92.8 %) 		6
(2.9% ) 		200
(97.1% ) 		6
(2.9% ) 		200
( 97.1% ) 		7
(3.4%) 		199
(96.6%)
TOTAL 72
(6.9%) 		964
(93.1%) 		58
( 5.6% ) 		978
( 94.4% ) 		54
(5.2% ) 		982
( 94.8% ) 		47
( 4.5%) 		989
( 95.5% ) 		34
(3.6%) 		999
(96.4%)
Result of
Man-Witney
test 		0.0001 0.836 0.014 0.021 0.073
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The Mann-Whitney U test showed that dimensions of Communication (0.0001), Gross Motor (0.014) and Problem - Solving (0.021) were significantly correlated with SES.

The relationship between prevalence of developmental delay and various socioeconomic levels was evaluated using univariate logistic regression models and Odds Ratio (OR) of various levels compared to the highest group. OR of developmental delay increased with lower

SES. The distribution of developmental delay based on different SES levels and OR and 95% confidence intervals are shown in the Table 4.

Table 4.

Univariate Logistic Regression models, Relationship between SES Variables and Developmental Delay

Socio- Eco Level OR P Value CI
Lower Upper
Level 1 1 0.003
Level 2 0.479 0.004 0.290 0.791
Level 3 0.930 0.796 0.538 1.608
Level 4 1.141 0.650 0.646 2.014
Level 5 1.011 0.968 0.581 1.762
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A multiple logistic regression models were used to study the relationship between SES variables and developmental delay after adjusting for the following factors: child’s age and gender; mother’s gravida, parity and abortion. By referencing the first SES level and significance of the second level of this variable, the OR of developmental delay versus normal child development is 60% lower in the second level compared to the first. The child’s gender had a significant impact on their development and the OR of developmental delay in girls was 50% lower than in boys. (P=0.029) (Table 5).

Table 5.

Multiple Logistic Regression Models, Relationship between SES Variables and Developmental Delay after Adjusting for the Following Factors: Child’s Age and Gender; Mother’s Gravida, Parity and Abortion

Socio- Eco Level OR P Value CI
Lower Upper
Level 1 0.0001
Level 2 0.405 0.001 0.241 0.680
Level 3 0.786 0.408 0.455 1.390
Level 4 1.039 0.898 0.582 1.853
Level 5 1.024 0.935 0.584 1.795
Girl
Sex of child
boy 		0.518 0.0001 0.367 0.730
Age of child 1.007 0.494 0.987 1.028
Number of Gravida 0.772 0.916 0.506 1.658
Number of Abortion 1.085 0.792 0.591 1.993
Number of Parity 1.332 0.373 0.708 2/505
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Discussion

The degree of developmental delay in children was 16.2%. Consistent with the study results; a prevalence rate of 16.3% was reported for developmental delay (32). A prevalence rate of 18% for developmental delay was reported in 4- to 60-month-old children from Tehran (30). This slight difference in reported prevalence rates can be attributed to different sample sizes and children’s age.

Family SES affected child development and a low SES was an independent risk factor for developmental delay.

A decrease in family SES significantly increased the OR of developmental delay. Results of some studies are in line with our results (4, 20, 50, 52). However, most of the studies on the effect of SES on the developmental status of children have ignored the role of the main risk factors (32, 69, 70, 72). Many of these studies have only considered the role of income, education, and career,and have ignored the role of other factors.

Children of lower SES aged 36-60 months of age were more susceptible to developmental delay in ASQ Screening Test. SES mostly affected child development in communication, gross motor and problem solving domains.

Fine motor skills were the most delayed skills, and the least delayed skills were in the personal-social domain (41). This discrepancy in the results may be due to children’s age and different sample sizes.

SES in univariate and multivariate models showed a significant correlation only between developmental delay and child’s gender after controlling other factors such as child’s age, and mother’s gravida, parity and abortions. Children grown in families with lower SES, have their cognitive and emotional development and psychological health at higher risk (61).

Low family SES negatively affected child development particularly their communicational development (62).

The present study also found the highest developmental delay in communication skills. The impact of SES were reported on cognitive and emotional development in children (63).

SES is associated with a wide range of health outcomes, and cognitive and socio emotional development outcomes (3). The short-term (18, 19) and long-term (17, 22, 63, 64) were reported impacts of poverty on early childhood development. In addition, a strong relationship between risks factors of SES and long-term cognitive and linguistic outcomes rather than with socio emotional outcomes (65-67).

Low SES is associated with learning environment of children and it might affect their cognitive skills and developmental outcomes (5).

The relationship of low SES was reported at birth time with school achievements and cognitive skills of children (68). SES during infancy affected children’s cognitive development at 5 yr old (69).

Language deficit was reported in poor children aged 36-72 months in comparison with non-poor children. In addition, non-poor children achieved higher scores in vocabulary test than children with low SES (70). Great differences were reported in building vocabulary skills between children with high SES and low SES (71).

An experimental study on 3573 children aged 1 to 5 yr in Argentina showed that higher family SES and mother’s education were correlated with better psychomotor skills in children aged over 1 year (72).

Effective factors on developing gross motor skills in children are maternal education, socio economic status, physical environment (73-75). Moreover, there is no evidence in literature supporting the hypothesis that SES and children development (62). The positive impact of environmental stimulations in child development is well addressed in many studies in which secure attachment and a rich environment are considered as protective factors for child development (23, 76-79).

Brain development can be adjusted by the quality of environmental conditions (17) and brain can quickly develop through neurogenesis, axon/dendrite growth, synaptogenesis, apoptosis, synaptic pruning, myelination and glycogenesis (80).

Magnetic resonance imaging (MRI) has lately been used to show direct impact of SES on brain structure in children. Lower SES has been associated with smaller volumes of grey matter in some parts of brain. Brain structure can be affected by unfavorable environmental conditions even when deprivation and stress are not very severe (81).

Some scientists employed electrophysiological measures to study the impacts of SES on brain development.

This might show differences in cognition even when no differences in behavioral measures are observed.

In addition, baseline EEG activities have been used to evaluate general differences of brain function at resting state. EEG can be used to measure brain maturation especially in loci responsible for executive functioning (82). The differences in resting EEG patterns were reported in Mexican pre-school children because of SES function (83-84). On the other hand, SES affects brain development through different mediators such as parental factors, parental care, cognitive stimulations, nutrition, stress, etc. (85). Nutrition, home-environment, child-parent interaction, facilitating and stimulating learning experiences are effective on child development because higher SES would lead to better learning environment and lower SES is a barrier for learning and accessing cognitive stimulations (such as having access to newspapers, books, toys) (3).

Poverty would bring insufficient food and inadequate sanitation, which can lead to increased infection and stunting in children. It would also cause lower levels of education, an increase in depression and stress level in mother (3, 86, 87) and provide inadequate stimulation at home (88). A different approach was used and explained unfavorable impacts of SES on development via parents’ decisions for dedicating resources such as money, time and energy (money that parents would spend on buying books and toys, and the time spent with their children for reading books, etc.). Such measures are parents’ investment for child development and provide required potentials for cognitive and linguistic skills of children (89).

Studies have also indicated an increase in cortisol levels (90, 91). Chronic high levels of cortisol affect nervous system and other systems (92). There is a region in brain involved in stress response like prefrontal cortex, damaged at high levels of cortisol (93-96). Children with lower SES experience were documented higher levels of environmental and psychological stressors (3).

On the other hand, parents with low SES have an increased risk of developing different psychological distress such as negative feelings of self-worth and depression symptoms (97). Depression can affect mother-child interaction and reduce developmental outcomes in social and cognitive domains (98, 99). Lower sense of responsibility in mothers is also associated with low income. As a result, factors that might increase mother’s stress level can act as a mediator in lower SES families (100). Moreover, children born in poor families are more exposed to unfavorable developmental conditions (such as living in crowded areas or slums and having bad neighbors) (101).

The positive impacts of environmental stimulations in relation to child development have been proved in other studies. Experiments on animals and children have shown secure attachment and rich environment are protective factors for child development. Moreover, some scientists have emphasized the existence of a relationship between SES and cognitive and linguistic learning of children through family simulations, number of siblings and number of family members who live together (62).

Under-five children who stay at home were more susceptible to developmental delays (62) though these impacts might be due to having less interaction and receiving less attention of parents, which in turn can reduce receiving environmental stimulations (3, 22, 23, 63, 102).

Babies who are surrounded with more people in the family have better gross motor skills because higher proportion of adult/children living together causes closer contact, hence, more stimulations are received associated with positive reactions in neuro psychomotor development (62).

One of the fundamental problems in evaluating SES and health is that data collection of qualitative variable such as income, family consumption or career is not easily possible thus, other proxies such as properties and housing are used (103,104).

Use of proxy measures can produce unreliable and unstable results because they show only a part of the overall impact. However, a combination of variables in PFA model helps quantify proxy variables, creates a measurable score for every individual, categorizes such quantitative scores, and determines SES level for each person (59, 105). Use of principal factor analysis is one of the strongest points of the present study. Therefore, fewer errors might occur in comparison with other methods based on weighting and people’s opinion. The current study used a combination of proxy variables to create an SES index, namely, family properties, residence price per square meter, the floor area of the housing unit, and the number of schooling years.

Findings of this study are limited to the mothers with kindergarten children.

In conclusion, it is necessary to implement interventions and preventive measures at family level to improve child development.

Conflict of interest

This paper is adapted from a Ph.D. dissertation by Mahbobeh Ahmadi Doulabi entitled “Investigating the Status and Contribution of Parent Involvement in Children’s Education in Social Determinants of Health on the Developmental Level of 36-60 month-Old Children in Tehran.” The dissertation, no. 9958.1.T.93.801, has been written under the supervision of Dr. Firouzeh Sajedi and approved by the Pediatric Neuro Rehabilitation Research Center, University of Social Welfare & Rehabilitation Sciences. The authors declare that there is no conflict of interest.

Acknowledgements

The researchers appreciate Welfare Organization of Tehran, and the authorities and instructors of affiliated kindergartens. Mothers and children whose participation made this study feasible are also greatly thanked.

Author’s Contribution

Ahmadi Doulabi M: Study concept and design, Development of original idea, data collection, Statistical analysis and writing the manuscript

Sajedi F: Study concept and design, Development of original idea, revision of the content, edition of manuscript and finalization.

Vameghi R: Study concept and design, Development of original idea, Study supervision

Mazaheri MA: Study concept and design, Development of original idea, Study supervision

Akbarzadeh Baghban AR: Study concept and design, Development of original, idea, Statistical analysis and interpretation of the results

All authors agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

References

  • 1.Haghdoost AA. Complexity of the Socioeconomic Status and its Disparity as a Determinant of Health. Int J Prev. 2012;3(2):75. [PMC free article] [PubMed] [Google Scholar]
  • 2.Behavioral and social sciences research. Measuring Socioeconomic Status. e-Source. 2013. Available from: http://www.esourceresearch.org.
  • 3.Bradley RH, Corwyn RF. Socioeconomic status and child development. Annu Rev Psychol. 2002;53(1):371–99. doi: 10.1146/annurev.psych.53.100901.135233. [DOI] [PubMed] [Google Scholar]
  • 4.de Moura DR, Costa JC, Santos IS, Barros AJ, Matijasevich A, Halpern R, et al. Risk factors for suspected developmental delay at age 2 years in a Brazilian birth cohort. Paediatr Perinat Epidemiol. 2010;24(3):211–21. doi: 10.1111/j.1365-3016.2010.01115.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Feinstein L. Inequality in the early cognitive development of British children in the 1970 cohort. Economica. 2003;70(277):73–97. [Google Scholar]
  • 6.Anderson LM, Shinn C, Fullilove MT, Scrimshaw SC, Fielding JE, Normand J, et al. The effectiveness of early childhood development programs: A systematic review. Am J Prev Med. 2003;24(3):32–46. doi: 10.1016/s0749-3797(02)00655-4. [DOI] [PubMed] [Google Scholar]
  • 7.Health CoSDo. Early child development: a powerful equalizer: final report for the World Health Organization’s Commission on the Social Determinants of Health. 2007. [Google Scholar]
  • 8.Sadock BJ, Sadock VA. Kaplan and Sadock’s synopsis of psychiatry. Behavioral sciences/clinical psychiatry. Lippincott Williams & Wilkins; 2011. [Google Scholar]
  • 9.Vameghi R, Hatamizadeh N, Sajedi F, Shahshahanipoor S, Kazemnejad A. Production of a native developmental screening test: the Iranian experience. Child Care Health Dev. 2010;36:340–5. doi: 10.1111/j.1365-2214.2009.01013.x. [DOI] [PubMed] [Google Scholar]
  • 10.Radomski MV, Latham CAT. Occupational therapy for physical dysfunction. Lippincott Williams & Wilkins; 2008. 197 pp. [Google Scholar]
  • 11.Myers KM, Collett B, Cheng K, Myers K.M. Child and Adolescent Psychiatry. Baltimore, Maryland: Lippincott Williams & Wilkins; 2007. Psychiatric Rating Scales; pp. 17–40. The Essentials. [Google Scholar]
  • 12.Siddiqi A, Hertzman E, Irwin LG, Hertzman C. Early child development: A powerful equalizer. Improving equity in health by addressing social determinants. 2012. pp. 115–141. Avaliable from: http://www.who.int.
  • 13.Marmot M, Friel S, Bell R, Houweling TA, Taylor S, Health CoSDo. Closing the gap in a generation: health equity through action on the social determinants of health. The Lancet. 2008;372(9650):1661–9. doi: 10.1016/S0140-6736(08)61690-6. [DOI] [PubMed] [Google Scholar]
  • 14.Commission on Social Determinants of Health. Closing the gap in a generation: health equity through action on the social determinants of health (final report) Geneva: World Health Organization ; 2008. [DOI] [PubMed] [Google Scholar]
  • 15.Regalado M, Halfon N. Primary care services promoting optimal child development from birth to age 3 years: review of the literature. Arch Pediatr Adolesc Med. 2001;155(12):1311–22. doi: 10.1001/archpedi.155.12.1311. [DOI] [PubMed] [Google Scholar]
  • 16.Kershaw P, Warburton B. A Comprehensive Policy Framework for Early Human Capital Investment in BC. 2009. Available from: http://www.vancouversun.com.
  • 17.Grantham-McGregor S, Cheung YB, Cueto S, Glewwe P, Richter L, Strupp B, et al. Developmental potential in the first 5 years for children in developing countries. The lancet. 2007;369(9555):60–70. doi: 10.1016/S0140-6736(07)60032-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Andraca Id, Pino P, La Parra Ad, Rivera F, Castillo M. Factores de riesgo para el desarrollo psicomotor en lactantes nacidos en óptimas condiciones biológicas. Rev Saude Publica. 1998;32(2):138–47. doi: 10.1590/s0034-89101998000200006. [DOI] [PubMed] [Google Scholar]
  • 19.Lima M, Eickmann S, Lima A, Guerra M, Lira P, Huttly S, et al. Determinants of mental and motor development at 12 months in a low income population: a cohort study in northeast Brazil. Acta Paediatr. 2004;93(7):969–75. doi: 10.1111/j.1651-2227.2004.tb18257.x. [DOI] [PubMed] [Google Scholar]
  • 20.Walker SP, Wachs TD, Gardner JM, Lozoff B, Wasserman GA, Pollitt E, et al. Child development: risk factors for adverse outcomes in developing countries. The lancet. 2007;369(9556):145–57. doi: 10.1016/S0140-6736(07)60076-2. [DOI] [PubMed] [Google Scholar]
  • 21.Guo G, Harris KM. The mechanisms mediating the effects of poverty on children’s intellectual development. Demography. 2000;37(4):431–47. doi: 10.1353/dem.2000.0005. [DOI] [PubMed] [Google Scholar]
  • 22.Chilton M, Chyatte M, Breaux J. The negative effects of poverty & food insecurity on child development. Indian J Med Res. 2007;126(4):262. [PubMed] [Google Scholar]
  • 23.Miller JE. Developmental screening scores among preschoolaged children: The roles of poverty and child health. J Urban Health. 1998;75(1):135–52. doi: 10.1007/BF02344935. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Glascoe FP. Early detection of developmental and behavioral problems. Pediatr Rev. 2000;21(8):272–80. doi: 10.1542/pir.21-8-272. [DOI] [PubMed] [Google Scholar]
  • 25.Rydz D, Srour M, Oskoui M, Marget N, Shiller M, Birnbaum R, et al. Screening for developmental delay in the setting of a community pediatric clinic: a prospective assessment of parent-report questionnaires. J Pediatr. 2006;118(4):e1178–e86. doi: 10.1542/peds.2006-0466. [DOI] [PubMed] [Google Scholar]
  • 26.Glascoe F. Early detection of developmental and behavioral problems. Pediatr Rev. 2000;21(8):272–80. doi: 10.1542/pir.21-8-272. [DOI] [PubMed] [Google Scholar]
  • 27.Sajedi F, Vameghi R, Habibollahi A, Lornejad H, Delavar B. Standardization and validation of the ASQ developmental disorders screening tool in children of Tehran city. Tehran Univ Med J. 2012;70(7) [Google Scholar]
  • 28.Shahshahani S, Vameghi R, Azari N, Sajedi F, Kazemnejad A. Validity and Reliability Determination of Denver Developmental Screening Test-II in 0-6 Year– Olds in Tehran. Iran J Pediatr. 2010;20(3):313. [PMC free article] [PubMed] [Google Scholar]
  • 29.Afraz F, Ahmadi M, Sajedi F, Akbarzadeh bagheban A. Development Status of 4-24 Months Children Born to Teenage Mothers Referred to Health Care Centers in Yasuj, 2013. YUMSJ. 2015;20(3):253–63. [Google Scholar]
  • 30.Shahshahani S, Vameghi R, Azari N, Sajedi F, Kazemnejad A. Comparing the Results of Developmental Screening of 4-60 Months Old Children in Tehran Using ASQ & PDQ. Iran Rehab J. 2011;9:3–7. [Google Scholar]
  • 31.Shaahmadi F, Khushemehri G, Arefi Z, Karimyan A, Heidari F. Developmental Delay and Its Effective Factors in Children Aged 4 to12 Months. Int J Pediatr. 2015;3(1.1):396–402. [Google Scholar]
  • 32.Karami K AL, Moridi F, Falah F, Bayat Z, Pourvakhshoori N. Evaluation criteria and factors associated with the development of one year old children in Khorramabad. J Pediatr Nurs 2015. 2015;1(3):57–64. [Google Scholar]
  • 33.Dorre F, Fattahi Bayat G. Evaluation of children’s development (4-60mo) with history of NICU admission based on ASQ in Amir kabir Hospital, Arak. J Ardabil Univ Med Sci. 2011;11(2):143–50. [Google Scholar]
  • 34.Sajedi F, Doulabi M, Vameghi R, Baghban A, Mazaheri MA, Mahmodi Z, Ghasemi E. Development of Children in Iran: A Systematic Review andMeta-Analysis. Glob J Health Sci. 2016;8(8):145–161. doi: 10.5539/gjhs.v8n8p145. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Tervo RC. Identifying patterns of developmental delays can help diagnose neurodevelopmental disorders. Clin Pediatr (Phila) 2006;45(6):509–17. doi: 10.1177/0009922806290566. [DOI] [PubMed] [Google Scholar]
  • 36.Sajedi F, Vameghi R, Kraskian Mujembari A. Prevalence of undetected developmental delays in Iranian children. Child Care Health Dev. 2014;40(3):379–88. doi: 10.1111/cch.12042. [DOI] [PubMed] [Google Scholar]
  • 37.Spencer N. Social, economic, and political determinants of child health. Pediatrics. 2003;112(Supplement 3):704–6. [PubMed] [Google Scholar]
  • 38.Rafiey H VM, Sajjadi H, Ghaed , Amini Gh. Family Income and Child Health in Iran: Recognition of Intermediary Variables’ Role using Sructured Equation Models. Hakim Res J. 2015(3):2010–2014. [Google Scholar]
  • 39.Poon JK, Larosa AC, Pai GS. Developmental delay: timely identification and assessment. Indian Pediatr. 2010;47(5):415–22. doi: 10.1007/s13312-010-0077-3. [DOI] [PubMed] [Google Scholar]
  • 40.Conger RD, Conger KJ, Martin MJ. Socioeconomic status, family processes, and individual development. J Marriage Fam. 2010;72(3):685–704. doi: 10.1111/j.1741-3737.2010.00725.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Sajedi F, Vameghi R, Mohseni Bandpei MA et al. Motor developmental delay in 7500 Iranian infants: Prevalence and risk factors. Iran J Child Neurol. 2009;3(3):43–50. [Google Scholar]
  • 42.Potijk MR, Kerstjens JM, Bos AF, Reijneveld SA, de Winter AF. Developmental delay in moderately preterm-born children with low socioeconomic status: risks multiply. J Pediatr. 2013;163(5):1289–95. doi: 10.1016/j.jpeds.2013.07.001. [DOI] [PubMed] [Google Scholar]
  • 43.Brooks-Gunn J, Duncan GJ. The effects of poverty on children. Future Child. 1997:55–71. [PubMed] [Google Scholar]
  • 44.CatL-TEoP. Children and the Long-Term Effects of Poverty. The connecticut commission on children. 2004. Jun, Available from: https://www.cga.ct.gov.
  • 45.Komro KA, Flay BR, Biglan A, Consortium PNR. Creating nurturing environments: A science-based framework for promoting child health and development within high-poverty neighborhoods. Clin Child Fam Psychol Rev. 2011;14(2):111–34. doi: 10.1007/s10567-011-0095-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Canadian Institute for Health Information and Canadian Population Health Initiative. Improving the Health of Canadians. Summary Report [electronic Resource]. Canadian Institute for Health Information. 2004. Available from: https://www.cihi.ca.
  • 47.Evans GW. The environment of childhood poverty. Am Psychol. 2004;59(2):77. doi: 10.1037/0003-066X.59.2.77. [DOI] [PubMed] [Google Scholar]
  • 48.Elbers J, Macnab A, McLeod E. Article originale. Can J Rural Med. 2008;13(1):9–14. [PubMed] [Google Scholar]
  • 49.Richter J, Janson H. A validation study of the Norwegian version of the Ages and Stages Questionnaires. Acta Paediatr. 2007;96(5):748–52. doi: 10.1111/j.1651-2227.2007.00246.x. [DOI] [PubMed] [Google Scholar]
  • 50.Glascoe FP. Screening for developmental and behavioral problems. Ment Retard Dev Disabil Res Rev. 2005;11(3):173–9. doi: 10.1002/mrdd.20068. [DOI] [PubMed] [Google Scholar]
  • 51.Squires J, Bricker D, Potter L. Revision of a parent-completed developmental screening tool: Ages and Stages Questionnaires. J Pediatr Psychol. 1997;22(3):313–28. doi: 10.1093/jpepsy/22.3.313. [DOI] [PubMed] [Google Scholar]
  • 52.Lindsay NM, Healy GN, Colditz PB, Lingwood BE. Use of the Ages and Stages Questionnaire to predict outcome after hypoxic - ischaemic encephalopathy in the neonate. J Paediatr Child Health. 2008;44(10):590–5. doi: 10.1111/j.1440-1754.2008.01388.x. [DOI] [PubMed] [Google Scholar]
  • 53.Yu LM, Hey E, Doyle LW, Farrell B, Spark P, Altman DG, et al. Evaluation of the Ages and Stages Questionnaires in identifying children with neurosensory disability in the Magpie Trial follow - up study. Acta Paediatr. 2007;96(12):1803–8. doi: 10.1111/j.1651-2227.2007.00517.x. [DOI] [PubMed] [Google Scholar]
  • 54.Vameghi R, Sajedi F, Mojembari AK, Habiollahi A, Lornezhad HR, Delavar B. Cross-cultural adaptation, validation and standardization of Ages and Stages Questionnaire (ASQ) in Iranian children. Iran J Public Health. 2013;42(5):522. [PMC free article] [PubMed] [Google Scholar]
  • 55.Fukuda Y, Nakamura K, Takano T. Municipal socioeconomic status and mortality in Japan: sex and age differences, and trends in 1973–1998. Soc Sci Med. 2004;59(12):2435–45. doi: 10.1016/j.socscimed.2004.04.012. [DOI] [PubMed] [Google Scholar]
  • 56.Morasae EK, Forouzan AS, Majdzadeh R, Asadi-Lari M, Noorbala AA, Hosseinpoor AR. Understanding determinants of socioeconomic inequality in mental health in Iran’s capital, Tehran: a concentration index decomposition approach. Int J Equity Health. 2012;11(1):1–13. doi: 10.1186/1475-9276-11-18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Rohani-Rasaf M, Moradi-Lakeh M, Ramezani R, Asadi- Lari M. Measuring socioeconomic disparities in cancer incidence in Tehran, 2008. SN:1513-7368 (Print); 1513- 7368 (Linking) Asian Pac J Cancer Prev. 2012;13(6):2955–60. doi: 10.7314/apjcp.2012.13.6.2955. [DOI] [PubMed] [Google Scholar]
  • 58.Moradi-Lakeh M, Ramezani M, Naghavi M. Equality in safe delivery and its determinants in Iran. Arch Iran Med. 2007;10(4):446–51. [PubMed] [Google Scholar]
  • 59.Krefis AC, Schwarz NG, Nkrumah B, Acquah S, Loag W, Sarpong N, et al. Principal component analysis of socioeconomic factors and their association with malaria in children from the Ashanti Region, Ghana. Malar J. 2010;9(1):201. doi: 10.1186/1475-2875-9-201. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Najafianzadeh M, Mobarak-Abadi A, Ranjbaran M, Nakhaei M. Relationship between the Prevalence of Food Insecurity and Some Socioeconomic and Demographic Factors in the Rural Households of Arak, 2014. Iran J Nutr Sci Food Technol. 2015;9(4):35–44. [Google Scholar]
  • 61.de Onis M, Blössner M, Villar J. Levels and patterns of intrauterine growth retardation in developing countries. Eur J Clin Nutr. 1998;52:S5–15. [PubMed] [Google Scholar]
  • 62.Paiva GSd, Lima ACVMd, Lima MdC, Eickmann SH. The effect of poverty on developmental screening scores among infants. Sao Paulo Med J. 2010;128(5):276–83. doi: 10.1590/S1516-31802010000500007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Najman JM, Aird R, Bor W, O’Callaghan M, Williams GM, Shuttlewood GJ. The generational transmission of socioeconomic inequalities in child cognitive development and emotional health. Soc Sci Med. 2004;58(6):1147–58. doi: 10.1016/s0277-9536(03)00286-7. [DOI] [PubMed] [Google Scholar]
  • 64.Evans GW, Kim P. Childhood poverty and health cumulative risk exposure and stress dysregulation. Soc Sci Med. 2007;18(11):953–7. doi: 10.1111/j.1467-9280.2007.02008.x. [DOI] [PubMed] [Google Scholar]
  • 65.Duncan GJ, Brooks-Gunn J. Consequences of growing up poor. Russell Sage Foundation; 1999. pp. 132–189. [Google Scholar]
  • 66.Duncan GJ, Yeung WJ, Brooks-Gunn J, Smith JR. How much does childhood poverty affect the life chances of children? Am Sociol Rev. 1998:406–23. [Google Scholar]
  • 67.Aber JL, Jones S, Cohen J. The impact of poverty on the mental health and development of very young children. 2nd ed. . New York, NY, US: Guilford Press; 2000. pp. 113–128. [Google Scholar]
  • 68.Stein AD, Behrman JR, DiGirolamo A, Grajeda R, Martorell R, Quisumbing A, et al. Schooling, educational achievement, and cognitive functioning among young Guatemalan adults. Food & Nutrition Bulletin. 2005;26(Supplement 1):46S–54S. doi: 10.1177/15648265050262S105. [DOI] [PubMed] [Google Scholar]
  • 69.Sigman M, McDonald MA, Neumann C, Bwibo N. Prediction of cognitive competence in Kenyan children from toddler nutrition, family characteristics and abilities. J Child Psychol Psychiatry. 1991;32(2):307–20. doi: 10.1111/j.1469-7610.1991.tb00309.x. [DOI] [PubMed] [Google Scholar]
  • 70.Paxson C, Schady N. Cognitive development among young children in Ecuador the roles of wealth, health, and parenting. J Hum Resour. 2007;42(1):49–84. [Google Scholar]
  • 71.Hart B, Risley TR. Meaningful differences in the everyday experience of young American children. Paul H Brookes Publishing Meaningful differences in the everyday experience of young American children; 1995. 268 pp. [Google Scholar]
  • 72.Lejarraga H, Pascucci MC, Krupitzky S, Kelmansky D, Bianco A, Martínez E, et al. Psychomotor development in Argentinean children aged 0–5 years. Paediatr Perinat Epidemiol. 2002;16(1):47–60. doi: 10.1046/j.1365-3016.2002.00388.x. [DOI] [PubMed] [Google Scholar]
  • 73.Najman J, Bor W, Morrison J, Andersen M, Williams G. Child developmental delay and socio-economic disadvantage in Australia: a longitudinal study. Soc Sci Med. 1992;34(8):829–35. doi: 10.1016/0277-9536(92)90252-l. [DOI] [PubMed] [Google Scholar]
  • 74.Nicholson JM, Lucas N, Berthelsen D, Wake M. Socioeconomic inequality profiles in physical and developmental health from 0–7 years: Australian National Study. J Epidemiol Community Health. 2010 doi: 10.1136/jech.2009.103291. jech. 2009.103291. [DOI] [PubMed] [Google Scholar]
  • 75.Berger SE, Theuring C, Adolph KE. How and when infants learn to climb stairs. Infant Behav Dev. 2007;30(1):36–49. doi: 10.1016/j.infbeh.2006.11.002. [DOI] [PubMed] [Google Scholar]
  • 76.Sajedi F, Barati H. The effect of Perceptual Motor Training on Motor Skills of preschool children. Iran Rehab J. 2014;12(19):30–40. [Google Scholar]
  • 77.Eickmann SH, Lima AC, Guerra MQ, Lima MC, Lira PI, Huttly SR, et al. Improved cognitive and motor development in a community-based intervention of psychosocial stimulation in northeast Brazil. Dev Med Child Neurol. 2003;45(08):536–41. doi: 10.1017/s0012162203000987. [DOI] [PubMed] [Google Scholar]
  • 78.Garrett P, Ng’andu N, Ferron J. Poverty experiences of young children and the quality of their home environments. Child Dev. 1994;65(2):331–45. [PubMed] [Google Scholar]
  • 79.Walker SP, Chang SM, Powell CA, Grantham-McGregor SM. Effects of early childhood psychosocial stimulation and nutritional supplementation on cognition and education in growth-stunted Jamaican children: prospective cohort study. The Lancet. 2005;366(9499):1804–7. doi: 10.1016/S0140-6736(05)67574-5. [DOI] [PubMed] [Google Scholar]
  • 80.Thompson RA, Nelson CA. Developmental science and the media: Early brain development. Am Psychol. 2001;56(1) doi: 10.1037/0003-066x.56.1.5. [DOI] [PubMed] [Google Scholar]
  • 81.Jednoróg K, Altarelli I, Monzalvo K, Fluss J, Dubois J, Billard C, et al. The influence of socioeconomic status on children’s brain structure. PLoS One. 2012;7(8):e42486. doi: 10.1371/journal.pone.0042486. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 82.Hackman DA, Farah MJ. Socioeconomic status and the developing brain. Trends Cogn Sci. 2009;13(2):65–73. doi: 10.1016/j.tics.2008.11.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 83.Otero GA. Poverty, cultural disadvantage and brain development: a study of pre-school children in Mexico. Electroencephalogr Clin Neurophysiol. 1997;102(6):512–6. doi: 10.1016/s0013-4694(97)95213-9. [DOI] [PubMed] [Google Scholar]
  • 84.Otero G, Pliego-Rivero F, Fernández T, Ricardo J. EEG development in children with sociocultural disadvantages: a follow-up study. Clin Neurophysiol. 2003;114(10):1918–25. doi: 10.1016/s1388-2457(03)00173-1. [DOI] [PubMed] [Google Scholar]
  • 85.Hackman DA, Farah MJ, Meaney MJ. Socioeconomic status and the brain: mechanistic insights from human and animal research. Nat Rev Neurosci. 2010;11(9):651–9. doi: 10.1038/nrn2897. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 86.Hamadani J, Grantham-McGregor S. Report of the family care indicators project: Validating the family psychosocial indicators in rural Bangladesh. Report to UNICEF Early Child Development Desk. 2004 [Google Scholar]
  • 87.Baker-Henningham H, Powell C, Walker S, Grantham- McGregor S. Mothers of undernourished Jamaican children have poorer psychosocial functioning and this is associated with stimulation provided in the home. Eur J Clin Nutr. 2003;57(6):786–92. doi: 10.1038/sj.ejcn.1601611. [DOI] [PubMed] [Google Scholar]
  • 88.Paxson CH, Schady NR. Cognitive development among young children in Ecuador: the roles of wealth, health and parenting: World Bank Policy Research Working, 2005 May. Paper 3605. Available from : http://econ.worldbank.org.
  • 89.Foster MA, Lambert R, Abbott-Shim M, McCarty F, Franze S. A model of home learning environment and social risk factors in relation to children’s emergent literacy and social outcomes. Early Child Res Q. 2005;20(1):13–36. [Google Scholar]
  • 90.Evans GW. A multimethodological analysis of cumulative risk and allostatic load among rural children. Dev Psychol. 2003;39(5):924. doi: 10.1037/0012-1649.39.5.924. [DOI] [PubMed] [Google Scholar]
  • 91.Lupien SJ, King S, Meaney MJ, McEwen BS. Can poverty get under your skin? Basal cortisol levels and cognitive function in children from low and high socioeconomic status. Dev Psychopathol. 2001;13(03):653–76. doi: 10.1017/s0954579401003133. [DOI] [PubMed] [Google Scholar]
  • 92.McEwen BS, Gianaros PJ. Stress-and allostasis-induced brain plasticity. Annu Rev Med. 2011;62:431. doi: 10.1146/annurev-med-052209-100430. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 93.Blair C. Stress and the Development of Self-Regulation in Context. Child Dev Perspect. 2010;4(3):181–8. doi: 10.1111/j.1750-8606.2010.00145.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 94.Liston C, McEwen B, Casey B. Psychosocial stress reversibly disrupts prefrontal processing and attentional control. Proc Natl Acad Sci. 2009;106(3):912–7. doi: 10.1073/pnas.0807041106. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 95.Lupien SJ, Maheu F, Tu M, Fiocco A, Schramek TE. The effects of stress and stress hormones on human cognition: Implications for the field of brain and cognition. Brain Cogn. 2007;65(3):209–37. doi: 10.1016/j.bandc.2007.02.007. [DOI] [PubMed] [Google Scholar]
  • 96.McEwen BS, Gianaros PJ. Central role of the brain in stress and adaptation: links to socioeconomic status, health, and disease. Ann N Y Acad Sci. 2010;1186(1):190–222. doi: 10.1111/j.1749-6632.2009.05331.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 97.Jack S, Philips D. From neurons to neighborhoods: The science of early childhood development. Washington, DC; press: National Academy Press; 2000. 289 pp. [PubMed] [Google Scholar]
  • 98.Sajedi F, Alizad V, Malekkhosravi G, Karimlou M, Vameghi R. Depression in mothers of children with cerebral palsy and its relation to severity and type of cerebral palsy. Acta Med Iranica. 2010;48(4):250–4. [PubMed] [Google Scholar]
  • 99.Murray L, Cooper PJ. Effects of postnatal depression on infant development. Arch Dis Child. 1997;77(2):99–101. doi: 10.1136/adc.77.2.99. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 100.Evans GW, Boxhill L, Pinkava M. Poverty and maternal responsiveness: The role of maternal stress and social resources. Int J Behav Dev. 2008;32(3):232–7. [Google Scholar]
  • 101.DiPietro JA. Baby and the brain: Advances in child development. Annu Rev Public Health. 2000;21(1):455–71. doi: 10.1146/annurev.publhealth.21.1.455. [DOI] [PubMed] [Google Scholar]
  • 102.Evans GW. Child development and the physical environment. Annu Rev Psychol. 2006;57:423–51. doi: 10.1146/annurev.psych.57.102904.190057. [DOI] [PubMed] [Google Scholar]
  • 103.McKenzie DJ. Measuring inequality with asset indicators. J Popul Econ. 2005;18(2):229–60. [Google Scholar]
  • 104.Ranjbaran M, Soori H, Etemad K, Khodadost M. Relationship between Socioeconomic Status and Health Status and Application of Principal Component Analysis. Journal of Jiroft University of Medical Sciences. 2014;1(1):9–19. [Google Scholar]
  • 105.Kolenikov S, Angeles G. Socioeconomic status measurement with discrete proxy variables: Is principal component analysis a reliable answer? Rev Income Wealth. 2009;55(1):128–65. [Google Scholar]

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