Abstract
Background
In urban areas, particularly among informal settlements, malnutrition and mental health disorders are recognized as key indicators of social inequality. Child malnutrition encompasses a wide range of developmental disorders. Mental disorders are also considered one of the main causes of the global burden of disease. This study aimed to investigate the nutritional status in children, mental health, and exposure to domestic violence among mothers living in the marginalized areas of Mashhad, northeast Iran.
Methods
This cross-sectional study analyzed data from 325863 individuals (children and mothers) living in the marginalized areas of Mashhad, registered in the Sina Electronic Health Record SINAEHR) system between 2016 and 2018. National reference standard values for underweight (weight-for-age), stunting (height-for-age), wasting, overweight, and obesity (weight-for-height) were used to define nutritional status. Binary and multinomial logistic regression models were applied to explore the associated factors with nutritional and mental health status. Data analysis was performed using SPSS software version 26.
Results
A total, 51.2% were boys and 48.8% were girls. Children with abnormal TSH were 20% more likely to be Stunting. Girls were 14% more likely to be underweight than boys (AOR = 1.14; 95% CI: 1.07–1.23). Maternal education and employment played a protective role in children’s nutritional indicators. Regarding mental health and domestic violence indicators, smoking was associated with an increased likelihood of developing mental health problems (AOR = 3.58; 95% CI: 3.26–3.93). No statistically significant association was found between alcohol consumption and domestic violence; mothers with low scores on the mental health assessment were more likely to experience domestic violence, and a significant association was observed in this regard.
Conclusions
Malnutrition and mental health problems remain significant challenges among children and mothers in marginalized areas. Strengthening maternal support, early identification, and integrated health interventions are crucial to reduce these disparities.
Keywords: Malnutrition, Mental health, Domestic violence, Child, Mothers, Suburban population, Iran
Introduction
Nutrition is a multifaceted phenomenon shaped by sociocultural, economic, medical, and dietary factors [1]. Each of these determinants independently influences human development throughout the lifespan [2]. When nutritional needs are unmet, both physical and mental health can be irreversibly impaired, resulting in various forms of malnutrition [3, 4]. Malnutrition encompasses stunting, wasting, underweight, micronutrient deficiencies, overweight, and obesity [5, 6]. In 2020, an estimated 149 million children under five years of age were stunted and 45 million were wasted. Meanwhile, overweight and obesity—representing another dimension of malnutrition—have become the second leading cause of death worldwide, accounting for approximately 300,000 deaths annually [7–10].
In national surveys of micronutrient status, 9.3% of girls and 7.8% of boys aged 15–23 months, and 11% of girls and 7.7% of boys aged 6 years were under weight. The prevalence of nutritional stunting in the 15–23-month age group was 15.1% among girls and 14.5% among boys, while in the 6-year age group, it reached 9.6% and 13.5%, respectively [11, 12]. These conditions not only elevate child morbidity and mortality but also impose substantial economic burdens due to decreased productivity and increased healthcare costs [13]. For instance, stunting alone results in an estimated annual global economic loss of US$548 billion, followed by low birth weight with US$344 billion. When overlapping factors such as poor breastfeeding are considered, preventable malnutrition costs the world at least US$761 billion annually, equivalent to about US$2.1 billion per day [14, 15].
To assess nutritional status, a variety of anthropometric tools and indices are employed, including growth charts, the Gomez classification (weight-for-age), and the McLaren index (weight-for-height) [16]. Anthropometric data are typically expressed as percentiles—indicating the percentage of the reference median—or as z-scores, representing standard deviations from the median. Key anthropometric indicators of nutritional status include wasting, underweight, and stunting [17].
Beyond its biological consequences, malnutrition is closely associated with mental health disorders. Socioeconomic deprivation and psychosocial stressors are recognized as major contributors to both nutritional deficiencies and mental disorders [18]. Mental and addictive disorders affect more than one billion people worldwide and account for 7% of the global burden of disease measured in disability-adjusted life years (DALYs) and 19% of total DALYs lost to disability. Depression, in particular, is among the leading causes of DALYs for both sexes [19, 20].
At the national level, three epidemiological studies have estimated the prevalence of mental disorders to be 21%, 17.1%, and 23.6%, respectively [21]. Furthermore, domestic violence is a serious public health concern; a national study reported an overall prevalence of 81.1% among couples and 84.5% among parents and children. Psychological violence was the most prevalent and severe form, affecting 75.5% of couples [22]. The risk factors for mental disorders can be broadly categorized into socioeconomic and anthropometric factors. Socioeconomic factors include gender, income, education level, unemployment, divorce, bereavement, and substance use, while anthropometric factors are related to body image and eating behaviors [23]. The interaction between these determinants varies significantly across regions and population groups [24]. In Iran, rapid urbanization and widening socioeconomic inequalities have intensified disparities in health outcomes [25].
Marginalized communities—particularly those in informal settlements—face numerous challenges, including poor housing, unemployment, poverty, limited education, and restricted access to healthcare services [26]. Mashhad, Iran’s second-largest metropolis, hosts one of the country’s largest marginalized populations, particularly in its northeastern districts. These neighborhoods experience rapid population growth, diverse migration patterns, and high poverty levels, making residents especially vulnerable to nutritional deficiencies and mental health issues. Accordingly, the present study aimed to investigate the nutritional status, mental health, and exposure to domestic violence among children and mothers living in the marginalized areas of Mashhad. By focusing on this high-risk population, the study seeks to identify prevailing health patterns and inform evidence-based strategies for prevention and intervention.
Methods
Study design and setting
This cross-sectional analytical study was conducted at Mashhad University of Medical Sciences (MUMS), northeastern Iran, using secondary data extracted from the Sina Electronic Health Record System (SinaEHR). The study protocol was approved by the Ethics Committee of MUMS.
Study population
The study population consisted of mothers and their children under five years of age residing in the marginalized urban outskirts of Mashhad who had visited MUMS-affiliated comprehensive health service centers between 2018 and 2024. Populations living in central metropolitan or urban areas were excluded from the final analysis.
Inclusion and exclusion criteria
Inclusion criteria were as follows: [1] complete electronic health records available in the SinaEHR system, and [2] availability of required demographic and clinical variables. Records with missing data on main study variables—such as child anthropometric indices or maternal mental health and domestic violence scores—were excluded.
Data quality and records management
The SinaEHR system is part of the National Health Information Infrastructure, supervised by the Iranian Ministry of Health and Medical Education. Data are entered by trained health staff at comprehensive health service centers using standardized electronic forms with built-in validation checks (e.g., range limits for anthropometric values). Data quality is ensured through regular supervisory audits, cross-validation, and random inspections conducted by MUMS monitoring teams. Health staff receive periodic training and certification to maintain data reliability [27].
Variables and operational definitions
Data were retrieved in two main areas:
Demographic variables: gender, place of residence (this variable reflects the official MUMS coding of marginal neighborhoods that may have different national census codes) including: metropolitan, rural, suburban, and city center, maternal education variable (illiterate, primary, secondary, university education) and maternal occupation were recorded in predefined categories (housewife, student, employee, farmer/worker, unemployed, self-employed). Health center: refers to comprehensive health service centers affiliated with Mashhad University of Medical Sciences (coded 1 to 5) that provide primary care and social services to the population covered by them.
-
2.
Clinical variables: Anthropometric indices for children under five (weight-for-age, height-for-age, and weight-for-height) were converted to z-scores based on World Health Organization reference standards. Thresholds were defined as follows: • Weight-for-age < − 2 SD: underweight • Height-for-age < − 2 SD: stunting • Weight-for-height < − 2 SD: wasting • +1 to + 3 SD: overweight • +3 SD: obesity Maternal body mass index (BMI) was calculated from routinely measured weight and height. In the SINAEHR system, thyroid function screening follows the national guidelines of the Iranian Ministry of Health. For neonates, normal TSH is defined as a serum TSH level of less than 5 mIU/L.
The HITS short questionnaire was designed by Sherin et al. (family physicians in the United States) with the aim of rapid screening for domestic violence. The questionnaire has 4 questions that focus on verbal and physical violence. Each question has 5 answer options, the minimum score for each question is 1 and the maximum score is 5, and the total score range is between 4 and 20. A score above 10 is considered positive and confirms the presence of violence. The reliability (i.e., internal consistency) and concurrent validity of the HITS instrument have been evaluated with a group of female patients who have visited their family physician, and the questionnaire has a high level of internal consistency, concurrent validity, and content and construct validity. Cronbach’s alpha was 0.87 [28]. The Kessler Psychological Assessment Questionnaire has six questions, which are: restlessness and restlessness, depression and sadness, hopelessness, worthlessness, hard work, and anxiety. The questionnaire is scored on a five-point scale from never (0) to always. The scale has a total score obtained by summing the item scores and indicates overall distress. The minimum and maximum scores are 0 and 24. Individuals who score 12 or more are considered positive. Cronbach’s alpha was also 0. 93 [29]. Alcohol consumption: This variable is derived from self-reported data collected during routine health visits, where individuals are asked about any history of alcohol consumption. Due to the legal and cultural context in Iran, reporting is limited. Therefore, alcohol consumption is categorized as “reported consumption” versus “unreported consumption.” We address this issue in the Discussion section. The variable of smoking status is recorded as current or former smokers based on standardized questions in the National Health Registry.
ِStatistical analysis
For dichotomous outcomes (maternal mental health, domestic violence, short stature and underweight coded as normal/abnormal), binary logistic regression models were used. For child nutritional outcomes (weight-for-height score), multinomial logistic regression was used because the dependent variable included more than two categories (underweight, normal, overweight and obese). Finally, adjustment was made for demographic and socioeconomic predictor variables. Incomplete or missing data were removed listwise and no imputation techniques were applied. To address potential multiple collinearities, we re-evaluated all predictor variables using the variance inflation factor (VIF) and no collinearity was observed. In order to examine the adjusted association of the main influential variable with the outcome under study, considering and controlling for the effect of confounding variables, variables with p values less than 0.25 were included in the model and the adjusted odds ratio (AOR) with 95% confidence intervals (CI) were reported. Statistical analyses were performed using SPSS version 26 software.
Results
Data from 325,863 active health records from health service centers in rural areas were extracted and analyzed. Of these, 51.2% (n = 166,776) were male and 48.8% (n = 159,087) were female. Regarding the educational status of the mothers, 2.9% were illiterate, 14.4% had primary education, 54.9% had a diploma, and 27.8% had a university education. In terms of employment status, 66.9% of the mothers were housewives and only 3.4% were employed in the government sector (employees). In terms of geographical distribution, 32.2% of the study population was covered by Comprehensive Health Service Center No. 1, 18.3% by Center No. 2, 31.1% by Center No. 3, and 18.4% by Center No. 5(Tables 1, 2, 3, 4 and 5.). Based on height-for-age index (Table 6), 2.02% of children were short-statured, of which 46.34% were boys and 53.66% were girls. The prevalence of underweight based on weight-for-age index was reported to be 2.33% (48.98% boys and 51.02% girls) (Table 7). Also, based on weight-for-height index, 3.8% of children were in the thin group (47.85% boys and 52.15% girls), 12.6% in the overweight group (45.26% boys and 54.74% girls), and 0.7% in the obese group (37.78% boys and 62.22% girls) (Table 8).
Table 1.
Distribution of maternal mental health status based on demographic and clinical factors
| Variable | Frequency (Percentage) | P-Value* | ||
|---|---|---|---|---|
| Psychological Assessment (Normal) | Psychological Assessment (Abnormal) | |||
| Gender | Male | 139,366 (48.77) | 5865 (49.25) | 0.306 |
| Female | 146,399 (51.23) | 6044 (50.75) | ||
| Place Of Residence | Metropolis | 121,826(42.63) | 3,862(32.43) | < 0.001 |
| Rural | 43,784(15.32) | 1,505(12.64) | ||
| Suburb | 118,423(41.44) | 6,497(54.56) | ||
| Uner_1_milon | 1,732(0.61) | 45(0.37) | ||
| Education Of Mother | Illiterate | 7,952(2.92) | 494(4.41) | < 0.001 |
| Primary School | 38,735(14.22) | 2,091(18.67) | ||
| Diploma | 149,274(54.80) | 6,425(57.38) | ||
| Academic Education | 76,442(28.06) | 2,188(19.54) | ||
| Job Of Mother | Housewife | 180,144(66.78) | 7,915(71.58) | < 0.001 |
| Student | 15,806(5.86) | 543(4.91) | ||
| Unemployed | 1,723(0.64) | 64(0.58) | ||
| Employee | 9,464(3.51) | 153(1.38) | ||
| Manual Worker/Farmer | 820(0.30) | 51(0.46) | ||
| Self-Employment | 61,820(22.82) | 2,332(21.09) | ||
| Mode Of Delivery | Vaginal Delivery | 143,427(50.19) | 5,730(48.11) | < 0.001 |
| Cesarean Delivery | 142,323(49.81) | 6,179(51.89) | ||
| BMI Of Mother | Wasting | 11,509(5.86) | 692(6.26) | < 0.001 |
| Normal | 86,503(44.07) | 4,692(42.37) | ||
| Overweight | 65,453(33.34) | 3,660(33.13) | ||
| Obesity | 32,832(16.73) | 2,005(18.15) | ||
| PKU New Born | Normal | 284,799(99.97) | 11,870(99.99) | 0.209 |
| Abnormal | 79(0.03) | 1(0.01) | ||
| TSH New Born | Normal | 267,872(94.03) | 11,148(93.89) | 0.540 |
| Abnormal | 17,008(5.97) | 725(6.11) | ||
| Alcohol Use | No | 285,623(99.95) | 11,886(99.81) | < 0.001 |
| Yes | 142(0.05) | 23(0.19) | ||
| Smoking | No | 282,304(98.79) | 11,134(93.49) | < 0.001 |
| Yes | 3,461(1.21) | 775(6.51) | ||
| Narcotic | No | 285,484(99.90) | 11,838(99.40) | < 0.001 |
| Yes | 281(0.10) | 71(0.60) | ||
| Health Center | Center 1 | 92,889(32.51) | 2,880(24.18) | < 0.001 |
| Center 2 | 52,090(18.23) | 2,294(19.26) | ||
| Center 3 | 88,204(30.86) | 4,496(37.75) | ||
| Center 5 | 52,582(18.40) | 2,239(18.81) | ||
| Weight For Height | Wasting | 10,728(3.83) | 470(4.02) | 0.290 |
| Normal | 231,984(82.80) | 9,727(83.15) | ||
| Overweight | 35,377(12.63) | 1,420(12.14) | ||
| Obesity | 2,087(0.74) | 81(0.69) | ||
| Height For Age | Normal | 279,999(97.98) | 11,646(97.79) | 0.148 |
| Stunting | 5,766(2.02) | 263(2.21) | ||
| Weight For Age | Normal | 279,133(97.68) | 11,600(97.41) | 0.052 |
| Underweight | 6,632(2.32) | 97.41(2.59) | ||
| Feeding Type | Exclusive Breast Feeding | 267,983(94.87) | 11,211(95.06) | 0.425 |
| Exclusive Formula Feeding | 11,596(4.1) | 457(3.87) | ||
| Combination Feeding | 2,897(1.03) | 126(1.07) | ||
Table 2.
Distribution of maternal domestic violence status among moter based on demographic and clinical factors
| Variable | Frequency (Percentage) | P-Value* | ||
|---|---|---|---|---|
| Domestic Violence (Normal) |
Domestic Violence (Abnormal) |
|||
| Gender | Male | 145,001 (48.77) | 230 (48.83) | 0.985 |
| Female | 152,202 (51.23) | 241 (51.17) | ||
| Place Of Residence | Metropolis | 125,552(42.24) | 136(28.87) | < 0.001 |
| Rural | 45,204 (15.21) | 85(18.05) | ||
| Suburb | 124,671(41.95) | 249(52.87) | ||
| Uner_1_milon | 1,776(0.60) | 1(0.21) | ||
| Education Of Mother | Illiterate | 7,952(2.97) | 24(5.76) | < 0.001 |
| Primary School | 40,749(14.39) | 77(18.47) | ||
| Diploma | 155,465(54.90) | 234(56.12) | ||
| Academic Education | 78,548(27.74) | 82(19.65) | ||
| Job Of Mother | Housewife | 187,762(66.96) | 297(71.91) | 0.004 |
| Student | 16,335(5.83) | 14(3.39) | ||
| Unemployed | 1,783(0.64) | 4(0.97) | ||
| Employee | 9,611(3.43) | 6(1.45) | ||
| Manual Worker/Farmer | 867(0.31) | 4(0.97) | ||
| Self-Employment | 64,064(22.83) | 88(21.31) | ||
| Mode Of Delivery | Vaginal Delivery | 148,935(50.11) | 222(47.13) | 0.196 |
| Cesarean Delivery | 148,253(49.89) | 249(52.87) | ||
| BMI Of Mother | Wasting | 12,171(5.88) | 30(7.16) | 0.682 |
| Normal | 91,009(43.98) | 186(44.39) | ||
| Overweight | 68,976(33.33) | 137(32.70) | ||
| Obesity | 34,771(16.81) | 66(15.75) | ||
| PKU New Born | Normal | 296,203(99.97) | 466(100.00) | 0.723 |
| Abnormal | 80(0.03) | 0(0.0) | ||
| TSH New Born | Normal | 278,575(94.02) | 445(95.49) | 0.181 |
| Abnormal | 17,712(5.98) | 21(4.51) | ||
| Alcohol Use | No | 297,039(99.94) | 470(99.79) | 0.148 |
| Yes | 164(0.06) | 1(0.21) | ||
| Smoking | No | 293,027(98.59) | 411(87.26) | < 0.001 |
| Yes | 4,176(1.41) | 60(12.74) | ||
| Narcotic | No | 296,855(99.88) | 467(99.15) | < 0.001 |
| Yes | 348(0.12) | 4(0.85) | ||
| Health Center | Center 1 | 95,665(32.19) | 104(22.08) | < 0.001 |
| Center 2 | 54,278(18.26) | 106(22.51) | ||
| Center 3 | 92,523(31.13) | 177(37.58) | ||
| Center 5 | 54,737(18.42) | 84(17.83) | ||
| Weight For Height | Wasting | 11,173(3.83) | 25(5.45) | 0.329 |
| Normal | 241,334(82.82) | 377(82.14) | ||
| Overweight | 36,743(12.61) | 54(11.76) | ||
| Obesity | 2,165(0.74) | 3(0.65) | ||
| Height For Age | Normal | 291,185(97.98) | 460(97.66) | 0.633 |
| Stunting | 6,018(2.02) | 11(2.34) | ||
| Weight For Age | Normal | 290,278(97.67) | 455(96.60) | 0.125 |
| Underweight | 6,925(2.33) | 16(3.40) | ||
| Feeding Type | Exclusive Breast Feeding | 278,754(94.88) | 440(94.83) | 0.830 |
| Exclusive Formula Feeding | 12,035(4.10) | 18(3.88) | ||
| Combination Feeding | 3,017(1.03) | 6(1.29) | ||
Table 3.
Distribution of height for age score in children based on demographic and clinical factors
| Variable | Frequency (Percentage) | P-Value* | ||
|---|---|---|---|---|
| Height For age (Normal) | Height For age (Stunting) | |||
| Gender | Male | 142,437 (48.64) | 2,794 (46.34) | < 0.001 |
| Female | 149,208 (51.36) | 3,235 (53.66) | ||
| Place Of Residence | Metropolis | 123,786(42.45) | 1,902(31.55) | < 0.001 |
| Rural | 44,017(15.09) | 1,272(21.10) | ||
| Suburb | 122,096(41.86) | 2,824(46.84) | ||
| Uner_1_milon | 1,746 (0.60) | 51(0.51) | ||
| Education Of Mother | Illiterate | 8178(2.94) | 268(4.72) | < 0.001 |
| Primary school | 39,674 (14.28) | 1152(20.28) | ||
| Diploma | 152,716(54.95) | 2983(52.51) | ||
| Academic Education | 77,352(27.83) | 1278(22.50) | ||
| Job Of Mother | Housewife | 184,130(66.90) | 3929(70.05) | < 0.001 |
| Student | 16,056(5.83) | 293(5.22) | ||
| Unemployed | 1740(0.63) | 47(0.84) | ||
| Employee | 9494(3.45) | 126(2.25) | ||
| Manual Worker/Farmer | 853(0.31) | 18(0.32) | ||
| Self-Employment | 62,956(22.87) | 1196(21.32) | ||
| Mode Of Delivery | Vaginal Delivery | 145,969(50.05) | 3,188 (52.89) | < 0.001 |
| Cesarean Delivery | 145,662(49.95) | 2,840(47.11) | ||
| BMI Of Mother | Wasting | 11,799(5.82) | 402(8.96) | < 0.001 |
| Normal | 89,189(43.97) | 2006(44.70) | ||
| Overweight | 67,721(33.38) | 1392(31.02) | ||
| Obesity | 34,149(16.83) | 688(15.33) | ||
| PKU New Born | Normal | 290,674(99.97) | 5995(99.93) | 0.058 |
| Abnormal | 76(0.03) | 4(0.07) | ||
| TSH New Born | Normal | 273,430(94.04) | 5,590(93.18) | 0.005 |
| Abnormal | 17,324(5.96) | 409(6.82) | ||
| Alcohol Use | No | 291,484(99.94) | 6,025(99.93) | 0.71 |
| Yes | 161(0.06) | 4(0.07) | ||
| Smoking | No | 287,495 (98.58) | 5,943(98.57) | 0.98 |
| Yes | 4,150(1.42) | 86(1.43) | ||
| Narcotic | No | 291,301(99.88) | 6,021(99.87) | 0.74 |
| Yes | 344(0.12) | 8(0.13) | ||
| Health Center | Center 1 | 94,164(32.29) | 1,605(26.62) | < 0.001 |
| Center 2 | 53,098(18.23) | 1,286(21.33) | ||
| Center 3 | 90,871(31.16) | 1,829(30.34) | ||
| Center 5 | 53,512(18.35) | 1,309(21.71) | ||
| Weight For Height | Wasting | 10,557(3.69) | 641(10.80) | < 0.001 |
| Normal | 237,107(82.92) | 4604(77.63) | ||
| Overweight | 36,209(12.66) | 588(9.91) | ||
| Obesity | 2071(0.72) | 97(1.63) | ||
| Domestic Violence | Normal | 291,185 (99.84) | 6,018 (99.82) | 0.63 |
| Abnormal | 460 (0.16) | 11(0.18) | ||
| Weight For Age | Normal | 287,247(98.49) | 3,486(57.82) | < 0.001 |
| Underweight | 4,398(1.51) | 2,543(42.18) | ||
| Feeding Type | Exclusive Breast Feeding | 273,647(94.90) | 5,547(93.53) | < 0.001 |
| Exclusive Formula Feeding | 11,767(4.08) | 286(4.82) | ||
| Combination Feeding | 2,925(1.01) | 98(1.65) | ||
| Mental Health Status | Normal | 279,999(96.01) | 5,766(95.64) | 0.148 |
| Abnormal | 11,646(3.99) | 263(4.36) | ||
Table 4.
Distribution of weight for age score in children based on demographic and clinical factors
| Variable | Frequency (Percentage) | P-Value* | ||
|---|---|---|---|---|
| Weight For Age (Normal) | Weight For Age (Underweight) | |||
| Gender | Male | 141,831 (48.78) | 3400 (48.98) | 0.74 |
| Female | 148,902 (51.22) | 3541 (51.02) | ||
| Place Of Residence | Metropolis | 123,496(42.48) | 2192(31.58) | < 0.001 |
| Rural | 43,879(15.09) | 1410(20.31) | ||
| Suburb | 121,626(41.83) | 3294(47.46) | ||
| Uner_1_milon | 1732 (0.60) | 45(0.65) | ||
| Education Of Mother | Illiterate | 8181(2.95) | 265(4.02) | < 0.001 |
| Primary school | 39,563 (14.28) | 1263(19.17) | ||
| Diploma | 152,098(54.91) | 3601(54.64) | ||
| Academic Education | 77,169(27.86) | 1461(22.17) | ||
| Job Of Mother | Housewife | 183,506(66.90) | 4553(69.78) | < 0.001 |
| Student | 15,984(5.83) | 365(5.59) | ||
| Unemployed | 1732(0.63) | 55(0.84) | ||
| Employee | 9466(3.45) | 151(2.31) | ||
| Manual Worker/Farmer | 850(0.31) | 21(0.32) | ||
| Self-Employment | 62,722(22.88) | 1380(21.15) | ||
| Mode Of Delivery | Vaginal Delivery | 145,677(50.11) | 3480 (50.14) | 0.95 |
| Cesarean Delivery | 145,042(49.89) | 3460(4.86) | ||
| BMI Of Mother | Wasting | 11,573(5.73) | 628(12.05) | < 0.001 |
| Normal | 88,776(43.92) | 2419(46.41) | ||
| Overweight | 67,600(33.44) | 1513(29.03) | ||
| Obesity | 34,185(16.91) | 652(12.51) | ||
| PKU New Born | Normal | 289,762(99.97) | 6907(99.91) | 0.002 |
| Abnormal | 74(0.03) | 6(0.09) | ||
| TSH New Born | Normal | 272,573(94.04) | 6447(93.26) | 0.007 |
| Abnormal | 17,267(5.96) | 466(6.74) | ||
| Alcohol Use | No | 290,573(99.94) | 6,936(99.93) | 0.55 |
| Yes | 160(0.06) | 5(0.07) | ||
| Smoking | No | 286,599 (98.58) | 6839(98.58) | 0.74 |
| Yes | 4131(1.42) | 102(1.47) | ||
| Narcotic | No | 290,390(99.88) | 6932(99.87) | 0.77 |
| Yes | 343(0.12) | 9(0.13) | ||
| Health Center | Center 1 | 93,869(32.29) | 1900(27.37) | < 0.001 |
| Center 2 | 53,148(18.28) | 1236(17.81) | ||
| Center 3 | 90,434(31.11) | 2266(32.65) | ||
| Center 5 | 53,282(18.33) | 15.39(22.17) | ||
| Weight For Height | Wasting | 7547(2.65) | 3651(52.65) | < 0.001 |
| Normal | 238,465(83.69) | 3246(46.81) | ||
| Overweight | 36,761(12.90) | 36(0.52) | ||
| Obesity | 2166(0.76) | 2(0.03) | ||
| Domestic Violence | Normal | 290,278 (99.84) | 6925 (99.77) | 0.12 |
| Abnormal | 455 (0.16) | 16(0.23) | ||
| Height For Age | Normal | 287,247(98.80) | 4398(63.36) | < 0.001 |
| Stunting | 3486(1.20) | 2453(36.64) | ||
| Feeding Type | Exclusive Breast Feeding | 272,817(94.91) | 6377(93.44) | < 0.001 |
| Exclusive Formula Feeding | 11,697(4.07) | 356(5.22) | ||
| Combination Feeding | 2931(1.02) | 92(1.35) | ||
| Mental Health Status | Normal | 279,133(96.01) | 6632(95.55) | 0.052 |
| Abnormal | 11,600(3.99) | 309(4.45) | ||
Table 5.
Distribution of weight for height score in children based on demographic and clinical factors
| Variable | Frequency (Percentage) | P-Value* | ||||
|---|---|---|---|---|---|---|
| Weight For Height (Wasting) | Weight for Height (Normal) |
Weight For Height (Overweight) | Weight For Height (Obesity) | |||
| Gender | Man | 5358(47.85) | 119644(49.50) | 16654(45.26) | 819(37.78) | <0.001 |
| Female | 5840(52.15) | 122067(50.50) | 20143(54.74) | 1349(62.22) | ||
| Place Of Residence | Metropolis | 3767(33.64) | 99924(41.34) | 17945(48.77) | 1261(58.16) | <0.001 |
| Rural | 2038(18.20) | 38058(15.75) | 4277(11.62) | 211(9.73) | ||
| Suburb | 5302(47.35) | 102249(42.30) | 14406(39.15) | 687(31.69) | ||
| Uner_1_milon | 91(0.81) | 1480(0.61) | 169(0.46) | 9(0.42) | ||
|
Education Of Mother |
Illiterate | 332(3.10) | 6968(3.02) | 963(2.76) | 27(1.31) | <0.001 |
| Primary School | 1845(17.22) | 33763(14.64) | 4302(12.34) | 210(10.17) | ||
| Diploma | 6150(57.37) | 127177(55.14) | 18473(52.98) | 1107(53.63) | ||
| Academic Education | 2392(22.31) | 62752(27.21) | 11131(31.92) | 720(34.88) | ||
| Job Of Mother | Housewife | 7459(70.27) | 153722(67.29) | 22165(64.24) | 1330(67.01) | <0.001 |
| Student | 630(5.93) | 13292(5.82) | 2021(5.86) | 122(5.97) | ||
| Unemployed | 72(0.68) | 1455(0.64) | 222(0.64) | 9(0.44) | ||
| Employee | 222(2.09) | 7606(3.33) | 1493(4.33) | 110(5.38) | ||
| Manual Worker/Farmer | 35(0.33) | 712(0.31) | 107(0.31) | 3(0.15) | ||
| Self-Employment | 2197(20.70) | 51653(22.61) | 8495(24.62) | 469(22.96) | ||
|
Mode of Delivery |
Vaginal Delivery | 5219(46.61) | 118851(49.17) | 20630(56.07) | 1326(61.16) | <0.001 |
| Cesarean Delivery | 5978(53.39) | 122847(50.83) | 16166(43.93) | 842(38.84) | ||
| BMI Of Mother | Wasting | 909(10.78) | 10426(6.11) | 712(3.04) | 26(2.01) | <0.001 |
| Normal | 4165(49.38) | 76641(44.92) | 8602(36.96) | 374(28.95) | ||
| Overweight | 2403(28.49) | 56318(33.01) | 8670(36.96) | 461(35.68) | ||
| Obesity | 958(11.36) | 27245(15.97) | 5475(23.34) | 431(33.36) | ||
| PKU New Born | Normal | 11140(99.96) | 240930(99.97) | 36700(99.99) | 2162(99.95) | 0.151 |
| Abnormal | 5(0.04) | 68(0.03) | 4(0.01) | 1(0.05) | ||
| TSH New Born | Normal | 10477(94.01) | 226514(93.99) | 34580(94.21) | 2048(94.68) | 0.215 |
| Abnormal | 668(5.99) | 14486(6.01) | 2125(5.79) | 115(5.32) | ||
| Alcohol Use | No | 11196(99.98) | 241576(99.94) | 36769(99.92) | 2168(100) | 0.082 |
| Yes | 2(0.02) | 135(0.06) | 28(0.08) | 0(0.00) | ||
| Smoking | No | 11051(98.69) | 238246(98.57) | 36281(98.60) | 2140(98.71) | 0.673 |
| Yes | 147(1.31) | 3465(1.43) | 516(1.40) | 28(1.29) | ||
| Narcotic | No | 11184(99.87) | 241436(99.89) | 36742(99.85) | 2162(99.72) | 0.048 |
| Yes | 14(0.13) | 275(0.11) | 55(0.15) | 6(0.28) | ||
| Health Center | Center 1 | 3159(28.21) | 77515(32.07) | 12385(33.66) | 817(37.68) | <0.001 |
| Center 2 | 1774(15.84) | 44420(18.638) | 6857(18.63) | 335(15.45) | ||
| Center 3 | 4020(35.90) | 74449(30.80) | 11606(31.54) | 718(33.12) | ||
| Center 5 | 2245(20.05) | 45327(18.75) | 5949(16.17) | 298(13.75) | ||
| Weight For Age | Normal | 7547(67.40) | 238465(98.66) | 36761(99.90) | 2166(99.91) | <0.001 |
| Under weight | 3651(32.60) | 3246(1.34) | 36(0.10) | 2(0.09) | ||
| Domestic Violence | Normal | 11173(99.78) | 241334(99.84) | 36743(99.85) | 2165(99.86) | 0.329 |
| Abnormal | 25(0.22) | 377(0.16) | 54(0.15) | 3(0.14) | ||
| Height For Age | Normal | 10557(94.28) | 237107(98.10) | 36209(98.40) | 2071(95.53) | <0.001 |
| Stunting | 641(5.72) | 4604(1.90) | 588(1.60) | 97(4.47) | ||
| Feeding Type | Exclusive Breast Feeding | 10475(94.99) | 227595(95.22) | 33867(93.04) | 1948(60.69) | <0.001 |
| Exclusive Formula Feeding | 452(4.10) | 9142(3.82) | 1998(5.49) | 168(7.82) | ||
| Combination Feeding | 100(0.91) | 2275(0.95) | 536(1.47) | 32(1.49) | ||
|
Mental Health Status |
Normal | 10728(95.80) | 231984(95.98) | 35377(96.14) | 2087(96.26) | 0.290 |
| Abnormal | 470(4.20) | 9727(4.02) | 1420(3.86) | 81(3.74) | ||
Table 6.
Factors associated with height for age score in children using multinomial logistic regression model
| Variable | Crude Odds Ratio | Adjusted Odds Ratio | |||||
|---|---|---|---|---|---|---|---|
| OR | CI | P-value | OR | CI | P-value | ||
| Gender | Male | Reference | |||||
| Female | 0.99 | (0.94–1.04) | 0.74 | - | - | - | |
| Smoking | No | Reference | |||||
| Yes | 1.03 | (1.26–0.84) | 0.741 | - | - | - | |
| Alcohol | No | Reference | |||||
| Yes | 1.30 | (0.53–3.18) | < 0.001 | 0.85 | (0.27–2.65) | 0.78 | |
| Narcotic | No | Reference | |||||
| Yes | 1.09 | (0.56–2.13) | 0.78 | - | - | - | |
| Mode Of Delivery | Vaginal Delivery | Reference | |||||
| Cesarean Delivery | 0.99 | (0.95–1.04) | 0.95 | - | - | - | |
| Mothers Age | - | 1.00 | (1.06–1.23) | 0.07 | 1.01 | (1.011–1.019) | < 0.001 |
| Feeding Type | Exclusive Breast Feeding | Reference | |||||
| Exclusive Formula Feeding | 1.30 | (1.16–1.45) | < 0.001 | 1.47 | (1.27–1.69) | < 0.001 | |
| Combination Feeding | 1.34 | (1.08–1.65) | < 0.001 | 1.10 | (0.77–1.58) | 0.56 | |
| TSH New Born | Normal | Reference | |||||
| Abnormal | 1.14 | (1.03–1.25) | < 0.001 | 1.20 | (1.07–1.35) | < 0.001 | |
| BMI Of Mother | Wasting | Reference | |||||
| Normal | 0.50 | (0.45–0.54) | < 0.001 | 0.50 | (0.46–0.55) | < 0.001 | |
| Overweight | 0.41 | (0.37–0.45) | < 0.001 | 0.41 | (0.37–0.45) | < 0.001 | |
| Obesity | 0.35 | (0.31–0.39) | < 0.001 | 0.33 | (0.29–0.37) | < 0.001 | |
| PKU New Born | Normal | Reference | |||||
| Abnormal | 3.40 | (1.47–7.81) | < 0.001 | 2.59 | (0.80–8.37) | 0.11 | |
| Education Of Mothers | Illiterate | Reference | |||||
| Primary school | 0.98 | (0.86–1.12) | 0.83 | 1.06 | (0.91–1.23) | 0.41 | |
| Diploma | 0.73 | (0.64–0.82) | < 0.001 | 0.92 | (0.79–1.06) | 0.28 | |
| Academic education | 0.58 | (0.51–0.66) | < 0.001 | 0.85 | (0.72–1.00.72.00) | 0.05 | |
| Job Of Mother | Housewife | Reference | |||||
| Student | 0.92 | (0.82–1.02) | 0.13 | 0.89 | (0.78–1.02) | 0.09 | |
| Unemployed | 1.27 | (0.97–1.67) | 0.07 | 1.26 | (0.93–1.69) | 0.12 | |
| Employee | 0.64 | (0.54–0.75) | < 0.001 | 0.74 | (0.58–0.95) | 0.02 | |
| Manual Worker/Farmer | 0.99 | (0.64–1.53) | 0.98 | 0.91 | (0.57–1.44) | 0.70 | |
| Self-Employment | 0.88 | (0.83–0.94) | < 0.001 | 0.97 | (0.90–1.05) | 0.51 | |
| Health Center | Center 1 | Reference | |||||
| Center 2 | 1.14 | (1.06–1.23) | < 0.001 | 0.98 | (0.90–1.07) | 0.75 | |
| Center 3 | 1.23 | (1.16–1.31) | < 0.001 | 10.25 | (1.16–1.35) | < 0.001 | |
| Center 5 | 1.42 | (1.33–1.52) | < 0.001 | 1.24 | (1.13–1.35) | < 0.001 | |
| Place Residence | Metropolis | Reference | |||||
| Rural | 1.81 | (1.69–1.93) | < 0.001 | 1.56 | (1.43–1.70) | < 0.001 | |
| Suburb | 1.52 | (1.44–1.61) | < 0.001 | 1.32 | (1.22–1.43) | < 0.001 | |
| Uner_1_milon | 1.46 | (1.08–1.97) | 0.01 | 1.42 | (1.01–1.98) | 0.04 | |
| Domestic Violence | Normal | Reference | |||||
| Abnormal | 1.47 | (0.89–2.42) | 0.128 | 1.34 | (0.77–2.35) | 0.29 | |
| Mental Health Status | Normal | Reference | |||||
| Abnormal | 1.12 | (0.99–1.25) | < 0.001 | 1.01 | (0.89–1.19) | 0.80 | |
Table 7.
Factors associated with weight for age score in children using multinomial logistic regression model
| Variable | Crude Odds Ratio | Adjusted Odds Ratio | |||||
|---|---|---|---|---|---|---|---|
| OR | CI | P-value | OR | CI | P-value | ||
| Gender | Male | Reference | |||||
| Female | 1.10 | (1.05–1.60) | < 0.001 | 1.14 | (1.07–1.23) | < 0.001 | |
| Smoking | No | Reference | |||||
| Yes | 1.00 | (0.80–1.24) | 0.98 | - | - | - | |
| Alcohol | No | Reference | |||||
| Yes | 1.20 | (0.44–3.24) | 0.71 | - | - | - | |
| Narcotic | No | Reference | |||||
| Yes | 1.12 | (0.55–2.26) | 0.74 | - | - | - | |
| Mode Of Delivery | Vaginal Delivery | Reference | |||||
| Cesarean Delivery | 0.89 | (0.84–0.93) | < 0.001 | 0.79 | (0.74–0.85) | < 0.001 | |
| Mothers Age | - | 1.00 | (0.99–1.00.99.00) | 0.54 | - | - | - |
| Feeding Type | Exclusive Breast Feeding | Reference | |||||
| Exclusive Formula Feeding | 1.19 | (1.06–1.35) | 0.003 | 1.17 | (0.97–1.40) | 0.08 | |
| Combination Feeding | 1.65 | (1.34–2.02) | < 0.001 | 1.62 | (1.12–2.33) | 0.01 | |
| TSH New Born | Normal | Reference | |||||
| Abnormal | 1.15 | (1.04–1.27) | < 0.001 | 1.15 | (1.00–1.32.00.32) | 0.04 | |
| BMI Of Mother | Wasting | Reference | |||||
| Normal | 0.66 | (0.59–0.73) | < 0.001 | 0.84 | (0.74–0.96) | 0.01 | |
| Overweight | 0.60 | (0.53–0.67) | < 0.001 | 0.78 | (0.68–0.90) | < 0.001 | |
| Obesity | 0.59 | (0.52–0.66) | < 0.001 | 0.75 | (0.64–0.87) | < 0.001 | |
| PKU New Born | Normal | Reference | |||||
| Abnormal | 2.55 | (0.93–6.97) | 0.06 | 0.50 | (0.52–4.89) | 0.55 | |
| Education OF Mother | Illiterate | Reference | |||||
| Primary School | 0.88 | (0.77–1.01) | 0.07 | 0.94 | (0.79–1.12) | 0.53 | |
| Diploma | 0.59 | (0.52–0.67) | < 0.001 | 0.72 | (0.61–0.86) | < 0.001 | |
| Academic education | 0.50 | (0.44–0.57) | < 0.001 | 0.70 | (0.58–0.84) | < 0.001 | |
| Job Of Mother | Housewife | Reference | |||||
| Student | 0.85 | (0.75–0.96) | 0.01 | 0.88 | (0.75–1.03) | 0.12 | |
| Unemployed | 1.26 | (0.94–1.69) | 0.11 | 1.05 | (0.72–1.54) | 0.76 | |
| Employee | 0.62 | (0.52–0.74) | < 0.001 | 0.87 | (0.66–1.16) | 0.36 | |
| Manual Worker/Farmer | 0.98 | (0.61–1.57) | 0.96 | 0.62 | (0.33–1.17) | 0.14 | |
| Self-Employment | 0.89 | (0.83–0.95) | < 0.001 | 0.97 | (0.89–1.07) | 0.61 | |
| Health Center | Center 1 | Reference | |||||
| Center 2 | 1.42 | (1.31–1.53) | < 0.001 | 1.24 | (1.12–1.37) | < 0.001 | |
| Center 3 | 1.18 | (1.10–1.26) | 0.<0.001 | 1.07 | (0.97–1.18) | 0.12 | |
| Center 5 | 1.43 | (1.33–1.54) | < 0.001 | 1.24 | (1.11–1.37) | < 0.001 | |
| Place Residence | Metropolis | Reference | |||||
| Rural | 1.88 | (1.75–2.02) | < 0.001 | 1.38 | (1.24–1.53) | < 0.001 | |
| Suburb | 1.50 | (1.41–1.59) | < 0.001 | 1.14 | (1.04–1.25) | < 0.001 | |
| Uner_1_milon | 1.15 | (0.80–1.65) | 0.42 | 1.24 | (0.58–1.41) | 0.67 | |
| Weight For Height | Wasting | Reference | |||||
| Normal | 0.31 | (00.29–0.34) | < 0.001 | 6.95 | (6.10–7.93) | < 0.001 | |
| Overweight | 0.26 | (0.23–0.29) | < 0.001 | 9.50 | (7.99–11.29) | < 0.001 | |
| Obesity | 0.77 | (0.61–0.95) | 0.02 | 31.49 | (23.50–42.50) | < 0.001 | |
| Weight For Age | Normal | Reference | |||||
| Under weight | 47.64 | (44.90–50.54.90.54) | < 0.001 | 10.42 | (9.62–11.19) | < 0.001 | |
| Domestic Violence | Normal | Reference | |||||
| Abnormal | 1.15 | (0.63–1.20) | 0.63 | 0.96 | (0.82–1.12) | 0.63 | |
|
Mental Health Status |
Normal | Reference | |||||
| Abnormal | 1.09 | (1.04–1.27) | 0.14 | 0.96 | (0.82–1.12) | 0.63 | |
Table 8.
Factors associated with weight for height score in children using multinomial logistic regression model
| Variable | Crude Odds Ratio | Adjusted Odds Ratio | |||||
|---|---|---|---|---|---|---|---|
| OR | CI | P-value | OR | CI | P-value | ||
| Gender | Male | Reference | |||||
| Female | 0.96 | (0.92–0.99) | 0.03 | 0.076 | (0.12 − 0.02) | < 0.001 | |
| Smoking | No | Reference | |||||
| Yes | 1.08 | (0.92–1.28) | 0.31 | - | - | - | |
| Alcohol | No | Reference | |||||
| Yes | 3.25 | (0.80–13.1) | 0.09 | 2.10 | (0.02–4.18) | 0.04 | |
| Narcotic | No | Reference | |||||
| Yes | 0.95 | (0.56–1.63) | 0.87 | - | - | - | |
| Type Of Delivery | Natural Birth | Reference | |||||
| Cesarean Section | 0.86 | (0.83–0.91) | < 0.001 | 0.01 | (0.06 − 0.03) | 0.5 | |
| Mothers Age | - | 0.99 | (0.99–1.00.99.00) | 0.49 | - | - | - |
| Feeding Type | Exclusive Breast Feeding | ||||||
| Exclusive Formula Feeding | 0.99 | (0.90–1.09) | 0.91 | - | - | - | |
| Combination Feeding | 1.13 | (0.92–1.38) | 0.23 | - | - | - | |
| TSH New Born | Normal | Reference | |||||
| Abnormal | 0.99 | (0.92–1.07) | 0.94 | - | - | - | |
| BMI Of Mother | Wasting | Reference | |||||
| Normal | 1.67 | (1.55–1.80) | < 0.001 | 0.31 | (0.22–0.39) | < 0.001 | |
| Overweight | 2.21 | (2.04–2.39) | < 0.001 | 0.52 | (0.43–0.62) | < 0.001 | |
| Obesity | 2.81 | (2.56–3.09) | < 0.001 | 0.73 | (0.62–0.84) | < 0.001 | |
| PKU New Born | Normal | Reference | |||||
| Abnormal | 0.58 | (0.23–1.43) | 0.54 | - | - | - | |
| Education Of Mother | Illiterate | Reference | |||||
| Primary school | 0.86 | (0.76–0.97) | 0.01 | 0.21 | (0.36 − 0.06) | < 0.001 | |
| diploma | 0.99 | (0.88–1.11) | 0.93 | 0.19 | (0.33 − 0.05) | < 0.001 | |
| Academic education | 1.30 | (1.15–1.46) | < 0.001 | 0.08 | (0.24 − 0.06) | 0.26 | |
| Job Of Mother | Housewife | Reference | |||||
| Student | 1.03 | (094-1.12.12) | 0.46 | 0.08 | (0.16–0.19) | 0.09 | |
| Unemployed | 0.98 | (0.77–1.24) | 0.90 | 0.006 | (0.29 − 0.27) | 0.96 | |
| Employee | 1.74 | (1.52–1.99) | < 0.001 | 0.23 | (0.02–0.43) | 0.02 | |
| Manual worker/farmer | 0.98 | (0.70–1.38) | 0.94 | 0.13 | (0.29–0.56) | 0.53 | |
| Self-employment | 1.16 | (1.10–1.21) | < 0.001 | 0.04 | (0.18 − 0.11) | 0.15 | |
| Health Center | Center 1 | Reference | |||||
| Center 2 | 1.01 | (0.95–1.07) | 0.66 | 0.21 | (0.14–0.29) | < 0.001 | |
| Center 3 | 0.75 | (0.71–0.78) | < 0.001 | 0.26 | (0.32- −0.19) | < 0.001 | |
| Center 5 | 0.79 | (0.75–0.84) | < 0.001 | 0.04 | (0.02- −0.12) | 0.20 | |
| Place Residence | Metropolis | Reference | |||||
| Rural | 0.66 | (0.62–0.69) | < 0.001 | 0.11 | (0.19–0.32) | < 0.001 | |
| Suburb | 0.69 | (0.63–0.67) | < 0.001 | 0.20 | (0.26 − 0.14) | < 0.001 | |
| Uner_1_milon | 0.57 | (0.46–0.71) | < 0.001 | 0.62 | (0.88 − 0.36) | < 0.001 | |
| Height For Age | Normal | Reference | |||||
| Stunting | 0.31 | (0.29–0.34) | < 0.001 | 1.91 | (1.78–2.04) | < 0.001 | |
| Weight For Age | Normal | Reference | |||||
| Under weight | 0.24 | (0.023–0.025) | < 0.001 | 4.18 | (4.26–4.10) | < 0.001 | |
| Domestic Violence | Normal | Reference | |||||
| Abnormal | 0.69 | (0.46–1.03) | 0.07 | 0.19 | (0.70 − 0.31) | 0.45 | |
| Mental Health Status | Normal | Reference | |||||
| Abnormal | 0.95 | (0.86–1.04) | 0.29 | - | - | - | |
Statistical analysis showed a significant difference between girls and boys in terms of short stature (p < 0.001). Children who were breastfed and formula-fed were 47% more likely to be short (AOR = 1.47; 95% CI: 1.27–1.69) and children with abnormal TSH levels were 20% more likely to be short. Also, maternal university education had a 15% protective effect against short stature (AOR = 0.85; 95% CI: 0.72–1.00) (Table 6). Children who were formula-fed were 62% more likely to be underweight than children who were breastfed (AOR = 1.62; 95% CI: 1.12–1.33). Higher maternal education (diploma and university) showed a protective effect against short stature. Girls were significantly more likely to be underweight than boys (AOR = 1.14; 95% CI: 1.07–1.23). Also, white-collar occupation and university education had a protective effect against weight-for-height disorder, and a significant association was observed between maternal pre-pregnancy body mass index (BMI) and all three nutritional indicators (Table 7). In the area of mental health, 3.9% of individuals required psychological assessment more. Of this group, 80.4% had secondary education and 71.5% were housewives. Comprehensive Health Service Center No. 3 had the highest share (37.7%) of cases identified as requiring mental health assessment. Center No. 3 was significantly associated with lower mental health assessment scores (AOR = 1.60; 95% CI: 1.51–1.69). Statistical analysis indicated that smoking was associated with an increased likelihood of mental disorders (AOR = 3.58; 95% CI: 3.26–3.93), while employment as an employee was identified as a protective factor (Table 9). Of those identified as exposed to domestic violence (0.1%), 80.3% had secondary education, 19.6% had university education, and 71.9% were housewives. No statistically significant association was found between alcohol consumption and domestic violence, however (Table 10), there was a statistically significant association between smoking and mental health score (p < 0.001).
Table 9.
Factors associated with maternal health status using multinomial logistic regression model
| Variable | Crude Odds Ratio | Adjusted Odds Ratio | |||||
|---|---|---|---|---|---|---|---|
| OR1 | CI2 | P-value | OR | CI | P-value | ||
| Gender | Male | Reference | |||||
| Female | 0.98 | (0.94–1.01) | 0.306 | - | - | - | |
| Smoking | No | Reference | |||||
| Yes | 5.67 | (5.24–6.15) | < 0.001 | 3.58 | (3.26–3.93) | < 0.001 | |
| Alcohol Use | No | Reference | |||||
| Yes | 3.89 | (2.50–6.04) | < 0.001 | 0.93 | (0.55–1.56) | 0.798 | |
| Narcotic | No | Reference | |||||
| Yes | 6.09 | (4.69–7.91) | < 0.001 | 2.31 | (1.69–3.16) | < 0.001 | |
| Mode Of Delivery | Vaginal Delivery | Reference | |||||
| Cesarean Delivery | 1.08 | (1.04–1.12) | < 0.001 | 0.98 | (0.98–1.03) | 0.623 | |
| Mother’s Age | - | 1.00 | (0.99–1.00.99.00) | 0.126 | 1.00 | (1.00–1.01.00.01) | < 0.001 |
| Feeding Type | Exclusive Breast Feeding | Reference | |||||
| Exclusive Formula Feeding | 0.94 | (0.85–1.03) | 0.22 | 1.11 | (0.99–1.24) | 0.052 | |
| Combination Feeding | 1.03 | (0.86–1.24) | 0.67 | 1.50 | (1.21–1.86) | < 0.001 | |
| TSH New Born | Normal | Reference | |||||
| Abnormal | 1.02 | (0.94–1.10) | 0.540 | - | - | - | |
| BMI Of Mother | Wasting | Reference | |||||
| Normal | 0.90 | (0.83–0.97) | 0.014 | 0.88 | (0.80–0.96) | 0.004 | |
| Overweight | 0.93 | (0.85–1.01) | 0.089 | 0.88 | (0.80–0.96.80.96) | 0.006 | |
| Obesity | 1.01 | (0.92–1.11) | 0.73 | 0.93 | (0.84–1.02) | 0.148 | |
| PKU New Born | Normal | Reference | |||||
| Abnormal | 0.30 | (0.04–2.18) | 0.23 | - | - | - | |
| Education Of Mother | Illiterate | Reference | |||||
| Primary School | 0.86 | (0.78–0.96) | 0.006 | - | - | - | |
| Diploma | 0.69 | (0.63–0.76) | < 0.001 | - | - | - | |
| Academic Education | 0.46 | (0.41–0.50) | < 0.001 | - | - | - | |
| Job Of Mother | Housewife | Reference | |||||
| Student | 0.78 | (0.71–0.85) | < 0.001 | 0.81 | (0.73–0.89) | < 0.001 | |
| Unemployed | 0.85 | (0.65–1.08) | 0.189 | 0.79 | (0.61–1.03) | 0.095 | |
| Employee | 0.36 | (0.31–0.43) | < 0.001 | 0.60 | (0.51–0.72) | < 0.001 | |
| Manual Worker/Farmer | 1.41 | (1.06–1.87) | 0.016 | 1.35 | (1.00–1.82.00.82) | 0.046 | |
| Self-Employment | 0.85 | (0.81–0.89) | < 0.001 | 0.99 | (0.94–1.04) | 0.77 | |
| Health Center | Center 1 | Reference | |||||
| Center 2 | 1.42 | (1.34–1.50) | < 0.001 | 0.99 | (0.93–1.06) | 0.97 | |
| Center 3 | 1.64 | (1.56–1.72) | < 0.001 | 1.60 | (1.51–1.69) | < 0.001 | |
| Center 5 | 1.37 | (1.29–1.45) | < 0.001 | 0.97 | (0.91–1.04) | 0.44 | |
| Place Residence | Metropolis | Reference | |||||
| Rural | 1.08 | (1.02–1.15) | 0.009 | 0.57 | (0.53–0.62) | < 0.001 | |
| Suburb | 1.73 | (1.66–1.80) | < 0.001 | 1.11 | (1.06–1.17) | < 0.001 | |
| Uner_1_milon | 0.81 | (0.60–1.10) | 0.190 | 0.64 | (0.47–0.88) | < 0.001 | |
| Weight For Height | Wasting | Reference | |||||
| Normal | 0.95 | (0.87–1.05) | 0.36 | 1.05 | (0.94–1.18) | 0.34 | |
| Overweight | 0.91 | (0.82–1.01) | 0.10 | 1.10 | (0.97–1.25) | 0.12 | |
| Obesity | 0.88 | (0.69–1.12) | 0.32 | 1.20 | (0.92–1.56) | 0.17 | |
| Height For Age | Normal | Reference | |||||
| Stunting | 1.09 | (0.96–1.24) | 0.148 | 0.97 | (0.83–1.13) | 0.737 | |
| Weight For Age | Normal | Reference | |||||
| Under Weight | 1.12 | (0.99–1.25) | 0.052 | 1.06 | (0.91–1.23) | 0.40 | |
1- Odds Ratio
2- Confidence interval
Table 10.
Factors associated with maternal domestic violence using multinomial logistic regression model
| Variable | Crude Odds Ratio | Adjusted Odds Ratio | |||||
|---|---|---|---|---|---|---|---|
| OR | CI | P-value | OR | CI | P-value | ||
| Gender | Male | Reference | |||||
| Female | 0.99 | (0.89–1.19) | 0.98 | - | - | - | |
| Smoking | No | Reference | |||||
| Yes | 10.24 | (7.79–13.45) | < 0.001 | 3.20 | (2.23–4.59) | < 0.001 | |
| Alcohol | No | Reference | |||||
| Yes | 3.85 | (0.53–27.5) | 0.17 | 0.97 | (2.23–7.44) | 0.98 | |
| Narcotic | No | Reference | |||||
| Yes | 7.30 | (2.71–19.65) | < 0.001 | 1.55 | (0.47–5.11) | 0.46 | |
| Mode Of Delivery | Vaginal Delivery | Reference | |||||
| Cesarean Delivery | 1.26 | (0.94–1.35) | 0.19 | 1.01 | (0.81–1.24) | 0.92 | |
| Mother’s Age | - | 1.00 | (0.99–1.01) | 0.55 | - | - | - |
| Feeding Type | Exclusive Breast Feeding | Reference | |||||
| Exclusive Formula Feeding | 0.94 | (0.59–1.51) | 0.82 | - | - | - | |
| Combination Feeding | 1.25 | (0.56–2.82) | 0.57 | - | - | - | |
| TSH New Born | Normal | Reference | |||||
| Abnormal | 0.74 | (0.47–1.15) | 0.18 | 0.69 | (0.41–1.16) | 0.16 | |
| BMI Of Mother | Wasting | Reference | |||||
| Normal | 0.82 | (0.56–1.21) | 0.34 | 0.98 | (0.63–1.53) | 0.96 | |
| Overweight | 0.80 | (0.54–1.19) | 0.28 | 0.96 | (0.61–1.52) | 0.89 | |
| Obesity | 0.77 | (0.49–1.18) | 0.23 | 0.89 | (0.54–1.46) | 0.65 | |
| PKU New Born | Normal | Reference | |||||
| Abnormal | 1 | - | - | - | - | - | |
| Education Of Mothers | Illiterate | Reference | |||||
| Primary School | 0.66 | (0.41–1.04) | 0.07 | 0.61 | (0.37–1.00.37.00) | 0.05 | |
| Diploma | 0.52 | (0.34–0.80) | < 0.001 | 0.65 | (0.41–1.02) | 0.06 | |
| Academic Education | 0.36 | (0.23–0.57) | < 0.001 | 0.67 | (0.40–1.11) | 0.12 | |
| Job Of Mother | Housewife | Reference | |||||
| Student | 0.54 | (0.31–0.92) | 0.02 | 0.48 | (0.25–0.91) | 0.02 | |
| Unemployed | 1.14 | (0.52–3.80) | 0.48 | 1.60 | (0.59–4.33) | 0.35 | |
| Employee | 0.39 | (0.17–0.88) | 0.02 | 0.80 | (0.32–2.00.32.00) | 0.64 | |
| Manual Worker/Farmer | 2.91 | (1.08–7.84) | 0.03 | 1.97 | (0.62–6.26) | 0.24 | |
| Self-Employment | 0.86 | (0.68–1.10) | 0.24 | 1.07 | (0.82–1.40) | 0.57 | |
| Health Center | Center 1 | Reference | |||||
| Center 2 | 1.79 | (1.37–2.35) | < 0.001 | 1.31 | (0.95–1.81) | 0.09 | |
| Center 3 | 1.75 | (1.38–2.24) | < 0.001 | 1.60 | (1.21–2.13) | < 0.001 | |
| Center 5 | 1.41 | (0.05–1.38) | 0.01 | 1.07 | (0.75–1.52) | 0.68 | |
| Place Residence | Metropolis | Reference | |||||
| Rural | 0.69 | (0.46–1.04) | 0.08 | 1.23 | (0.89–1.69) | 0.20 | |
| Suburb | 0.65 | (0.40–1.05) | 0.08 | 1.10 | (0.85–1.43) | 0.44 | |
| Uner_1_milon | 0.61 | (0.18–2.05) | 0.43 | 0.51 | (0.70–3.72) | 0.51 | |
| Weight For Height | Wasting | Reference | |||||
| Normal | 0.69 | (0.46–1.04) | 0.08 | 0.89 | (0.52–1.50) | 0.66 | |
| Overweight | 0.65 | (0.40–1.05) | 0.08 | 0.90 | (0.49–1.65) | 0.75 | |
| Obesity | 0.61 | (0.18–2.05) | 0.43 | 1.14 | (0.32–4.00.32.00) | 0.83 | |
| Height For Age | Normal | Reference | |||||
| Stunting | 1.15 | (0.63–2.10) | 0.63 | - | - | - | |
| Weight For Age | Normal | Reference | |||||
| Under Weight | 1.47 | (0.89–2.42) | 0.12 | 1.37 | (0.75–2.52) | 0.29 | |
|
Mental Health Status |
Normal | Reference | |||||
| Abnormal | 18.47 | (15.3–22.09.3.09) | < 0.001 | 10.68 | (8.59–13.29) | < 0.001 | |
Discussion
The present study examined the prevalence and determinants of malnutrition (underweight, stunting, wasting, overweight, and obesity) among children under five, as well as factors associated with maternal mental health and domestic violence in marginalized areas of Mashhad. The findings confirmed that malnutrition remains a major public health concern in these communities and is strongly influenced by socioeconomic and family-related factors. The average age of participating mothers was 31.7 years (SD = 5.96). Low maternal education, smoking, substance use, maternal age, BMI, and employment status emerged as key factors associated with both mental health and child nutritional outcomes. The prevalence of stunting, underweight, wasting, overweight, and obesity was 2.03%, 2.33%, 3.84%, 12.6%, and 0.7%, respectively. These rates are lower than those reported in the study by Mousavi et al., which may be explained by several factors. First, improvements in maternal and child health programs and nutritional interventions in recent years may have reduced the prevalence of malnutrition. Second, regional differences in socioeconomic conditions, dietary habits, and healthcare access between Mashhad and other provinces may contribute to variability. Third, methodological differences, including the use of secondary health record data versus primary surveys, could also explain the observed discrepancies. Moreover, local interventions implemented in Mashhad’s marginalized neighborhoods, such as enhanced maternal-child health services, may have mitigated undernutrition compared with earlier findings. In the aforementioned study, the prevalence of wasting was reported as 19.2%, overweight was reported as 8.4%, and obesity was reported as 7.4% in preschool children, and no significant relationship was observed between gender and nutritional status [15]. However, in the current study, a significant relationship was observed between gender and nutritional indicators (weight-for-height and weight-for-age). Also, in Fars Province (2017–2018), the prevalence of stunting was reported as only 2% (a cross-sectional study on 606 children under five years of age), which is also consistent with this study. Abnormal levels of thyroid-stimulating hormone (TSH) may contribute to growth failure through several biological mechanisms. Thyroid hormones play a critical role in regulating metabolism, bone growth, and skeletal maturation in early childhood. Elevated TSH levels—often indicative of subclinical or overt hypothyroidism—can reduce circulating thyroxine (T4) and triiodothyronine (T3), leading to decreased protein synthesis, disruption of growth plates, and delayed bone formation. These processes collectively result in slower linear growth and short stature.In this study, low birth weight, family size, maternal education, and paternal occupation were identified as significant risk factors. These findings confirm that family socioeconomic status can play a significant role in the occurrence of developmental disorders [30]. In the present study, there was a significant association between stunting, underweight, male gender, maternal age and BMI, and formula feeding, and high maternal education had a protective role in the occurrence of stunting and underweight.
Consistent with international evidence from Mumbai, our study found that male gender, low maternal education, maternal age, and low birth weight were significant predictors of undernutrition [31]. Employment also showed a protective effect: mothers working as clerks had children with lower odds of underweight, overweight, and obesity. Significant differences were observed between catchment areas of health centers (particularly Centers 2, 3, and 5), indicating the importance of neighborhood-level socioeconomic context. Similar to findings from Ardabil, parental education and occupation were strong determinants of child nutrition [32], emphasizing the role of cultural and geographical variations in shaping malnutrition patterns. However, it is important to note that the cross-sectional design limits our ability to determine causal pathways. For instance, while smoking may contribute to poor mental health or increase the risk of domestic violence, the reverse could also be true. Longitudinal studies are therefore required to clarify these temporal and causal relationships. Higher rates of domestic violence were observed among women attending Comprehensive Health Service Center 3, possibly reflecting contextual socioeconomic vulnerabilities in that area. Regarding generalizability, the findings are limited to mothers and children in the marginalized areas of Mashhad and may not represent other urban centers or rural populations in Iran.
Low maternal education, smoking, substance use, maternal age, and overweight status were all significantly associated with lower mental health scores. These findings align with previous national research, such as Dolatian et al., who reported a high prevalence of domestic violence—especially emotional abuse (84.4%)—among Iranian women [33], and Noheja et al., who found significant associations between demographic factors (age, education, employment, and residence) and domestic violence [34]. A 2023 national survey of 24,584 Iranians aged ≥ 15 reported a domestic violence prevalence of 11.4%, significantly associated with female gender, younger age, lower education, unemployment, and suspected mental disorders [35]. Similarly, a meta-analysis of 31 studies involving 15,514 participants estimated domestic violence prevalence in Iran at 66%, with marked regional variations [36]. A 2006 cross-sectional study in Tehran reported a 35.7% prevalence of domestic violence among married women, with victims 3.5 times more likely to suffer from psychiatric disorders such as depression and anxiety than the general population [37].Other studies have also linked domestic violence to depression, anxiety, and poor mental health outcomes among women [38].
Global evidence further confirms that intimate partner violence remains widespread, particularly in low- and middle-income countries, where socioeconomic disparities exacerbate its prevalence [39, 40].From a policy perspective, these findings underscore the need for integrated interventions that address both nutritional and psychosocial determinants of health. Strengthening maternal education, integrating domestic violence and mental health screening into routine primary care, and expanding community-based counseling and support programs are essential steps. In addition, social protection policies targeting poverty, unemployment, and housing insecurity in marginalized areas can indirectly improve child nutrition and maternal well-being. Overall, this study contributes to a deeper understanding of the interconnected nature of malnutrition, mental health, and domestic violence in disadvantaged urban settings. Addressing these challenges requires coordinated action among policymakers, healthcare providers, and community organizations to design evidence-based, multisectoral interventions that simultaneously target biological, behavioral, and social determinants of health. Finally, it should be noted that alcohol consumption data in Iran are subject to underreporting due to cultural and legal restrictions. Consequently, the lack of a significant association between alcohol use and domestic violence in this study likely reflects data limitations rather than a true absence of relationship.
Conclusion
This study demonstrated that malnutrition and maternal mental health challenges remain important public health concerns among mothers and children living in the marginalized areas of Mashhad. The prevalence of underweight, stunting, and wasting was lower than reported in some previous studies, which may reflect regional differences, methodological variation, or the impact of recent health interventions. Low maternal education, maternal body mass index, and residential setting emerged as key determinants of child nutritional status, while poor mental health and exposure to domestic violence were strongly associated with socioeconomic and behavioral risk factors such as smoking. Although migrants are part of the marginalized population in Mashhad, our study was not designed to specifically investigate migration-related health disparities; therefore, the findings should be interpreted in the broader context of urban marginalization.
From a policy perspective, strengthening maternal education, expanding access to routine screening for domestic violence and mental health problems, and integrating nutritional support into primary health care are critical steps. Multi-sectoral approaches, including collaboration with governmental and non-governmental organizations to provide free counseling services and improve socioeconomic conditions, could help reduce these disparities. Future research should replicate this work in other urban centers and rural areas of Iran, using longitudinal designs to clarify causal pathways and better inform evidence-based interventions.
Limitations
This study has several limitations. First, despite the large overall sample size, certain subgroups—such as mothers who reported alcohol or drug use—were small in number, which may reduce the reliability and precision of the estimates. Second, the cross-sectional design precludes causal inference; longitudinal studies are needed to clarify temporal and causal pathways. Third, the findings are limited to mothers and children living in suburban neighborhoods of Mashhad and may not be generalizable to rural populations or other urban areas in Iran. Finally, the system only records general demographic characteristics (such as age, sex, place of residence, education), anthropometric and nutritional indicators, etc., and does not record information about ethnicity, quality of marital or family relationships, or specific occupational exposures and work shifts.
Acknowledgements
The authors also thank the study participants and the system of Registration and Classification of the causes of death of Iran who helped to collect these data.
Founding
This work was financially supported by vice-chancellor for research of Mashhad University of Medical Sciences (MUMS). The funding sources had no role in the design and conduct of the study, collection, management, analysis, interpretation of the data and decision to submit the manuscript for publication.
Authors’ contributions
Methodology: E.M.F. and M.S. Formal analysis: S.E. and M.S. Investigation: S.E. and M.A. and E.M.F. Writing original draft: S.E. and N.KH and M.D. Supervision: M.D. Project administration: M.D. All authors reviewed the manuscript, revised it critically for important intellectual content and approved the final manuscript draft.
Data availability
The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
The study protocol has been approved by the Institutional Review Board (IRB) of the Mashhad University of Medical Sciences (MUMS), Mashhad, Iran (IR.MUMS.FHMPM.REC.1402.207). The data used in this study were anonymized before its use. According to the Human Research Review & Ethics Committee, there was no need for informed consent, because the present research is a type of secondary and register-based data analysis. All methods in our study were performed in accordance with the relevant guidelines and regulations and have been performed in accordance with the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.WHO. Fact sheets: malnutrition. In fact, sheets: malnutrition [Internet]. 2021 [cited 4 Jan 2023.
- 2.Dent E, Wright ORL, Woo J, Hoogendijk EO. Malnutrition in older adults. Lancet. 2023;401(10380):951–66. [DOI] [PubMed] [Google Scholar]
- 3.Lachance L, Sean Martin M, Kaduri P, Godoy-Paiz P, Ginieniewicz J, Tarasuk V, et al. Food insecurity, diet quality, and mental health in culturally diverse adolescents. Ethnicity and Inequalities in Health and Social Care. 2014;7(1):14–22. [Google Scholar]
- 4.Noorbala AA, Damari B, Riazi Isfahani S. Evaluation of mental disorders incidence trend in Iran. Daneshvar Med [Internet]. 2014;21(112):unpaged. [Google Scholar]
- 5.Pourali S, Ghadimi A, Khorshodian N, Avazpour M, Malekzadeh J. An analytical study of complementary feeding pattern among healthy and failure to thrive children in Boyer-Ahmad County: a matched case-control study. Armaghane Danesh. 2022;26(5):815–26. [Google Scholar]
- 6.World Health Organization, United Nations Children’s Fund (UNICEF) & World Bank. (2021) . Levels and trends in child malnutrition: UNICEF / WHO / The World Bank Group joint child malnutrition estimates: key findings of the 2021 edition. World Health Organization10. Katoch OR. Determinants of malnutrition among children: A systematic review. Nutrition. 2022; 96:111565. [DOI] [PubMed]
- 7.Tadayyon M, Hoseini M, Rahmanian S, Abdollahzadeh P, Zahedi R. The prevalence of malnutrition in children under 6 in Southern Iran from 2018 to 2023: a population-based study author. J Health Popul Nutr. 2025;44(1):4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.HABICHT J-P. ET AL. Height and weight standards for pre-school children. How Relevant Are Ethnic Differences Growth potential? Lancet. 1974;1:611–5. [DOI] [PubMed] [Google Scholar]
- 9.Nouri Saeidlou S, Babaei F, Ayremlou P. Prevalence of malnutrition in children under 5 years old in Salma’s, and comparing to Ravansar and Samirom. RJMS. 2014;21(124):37–43. [Google Scholar]
- 10.Hosseini F, Gorgi Y, Javadzadeh A. The effectiveness of buckroyd’s group-based therapeutic approach on increasing self-esteem and improving eating attitude of obese-20 to 30-year-old females in Esfahan. J Educ Community Health. 2016;3(1):43–50. [Google Scholar]
- 11.Ofori-Asenso R, Agyeman AA, Laar A, Boateng D. Overweight and obesity epidemic in Ghana—a systematic review and meta-analysis. BMC Public Health. 2016;16:1239. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Björntorp P. International Textbook of Obesity. Chichester: John Wiley & Sons Ltd; 2001. p. 42–50. [Google Scholar]
- 13.Akseer N, Tasic H, Onah MN, Wigle J, Rajakumar R, Sanchez-Hernandez D, et al. Economic costs of childhood stunting to the private sector in low-and middle-income countries. E Clin Med. 2022;45:101320. pmid:35308896. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Jain S, Ahsan S, Robb Z, Crowley B. Dylan Walters,Health Policy and Planning, Volume 39, Issue 8, October 2024; 819–830. [DOI] [PMC free article] [PubMed]
- 15.Gaynor E, Sullivan P. Nutritional status and nutritional management in children with cancer. Arch Dis Child. 2015;100(12):1169–72. [DOI] [PubMed] [Google Scholar]
- 16.Nemati S, Narimani M, Gannadiasl F, Hashtjin GS. Comparison effect of SMN method and low-calorie diet (LCD) on lose weight and enhance the self-esteem of people with overweight. Örgütsel Davranış Araştırmaları Dergisi. 2018;3(2):1–9. [Google Scholar]
- 17.Torun B, Viteri FE. Energy requirements of preschool children and effects of varying energy intakes on protein metabolism. Food Nutr Bull Suppl. 1984;5:229–41. [Google Scholar]
- 18.WATERLOW JC, ET AL. The presentation and use of height and weight data for comparing the nutritional status of groups of children under the age of 10 years. Bull World Health Organ. 1979;55:489–98. [PMC free article] [PubMed] [Google Scholar]
- 19.Alonso J, Chatterji S, He Y, editors. The burdens of mental disorders: global perspectives from the WHO world mental health surveys. Cambridge University Press; 2013.
- 20.Rehm J, Shield KD. Global burden of disease and the impact of mental and addictive disorders. Curr Psychiatry Rep. 2019;21:10. [DOI] [PubMed] [Google Scholar]
- 21.Noorbala AHMADALI, Damari BEHZAD, Riazi Isfahani SAHAND. Evaluation of mental disorders incidence trend in Iran. DANESHVAR MEDICINE. 2014;21(112):0–0. [Google Scholar]
- 22.Sohanian Haghighi Mohsen, Faizi Iraj. Description of domestic violence in the Iranian family. Research of deviance and social problems. 2023;6:1–31. [Google Scholar]
- 23.Binsinger C, Laure P, Ambard M. Regular extra curricular sports practice does not prevent moderate or severe variation in self-steem or trait anxiety in early adolescents. J Sports Sci Med. 2006;5(1):123–9. [PMC free article] [PubMed] [Google Scholar]
- 24.Egan M, Daly M, Delaney L. Adolescent psychological distress, unemployment, and the great recession: evidence from the National longitudinal study of youth 1997. Soc Sci Med. 2016;156:98–105. [DOI] [PubMed] [Google Scholar]
- 25.Akbari MAHMOOD, Eltiyaminia Reza. Analysis of effective factor in quality of life and well-being in Iran Metropolis. Geography. 2021;19(70):81–96. [Google Scholar]
- 26.Hosseini S, Yasin. Sociological study of the Suburban-life pattern and its impact on sustainable development and health of Kurdistan, Iran (December 30, 2018). OIDA Int J Sustainable Dev. 2018;11(12):21–8. [Google Scholar]
- 27.Norouzi M, Amiri, Zahra FM, Ehsan. Hoseini Seyed Javad,Khosravi Asl, Tahereh Advancing Healthcare Infrastructure: The Features of Iran’s Sina Electronic Health Record System,Journal Article,2024,J Epidemiol Health System J,48–54,10.34172.26105.11.
- 28.Sherin KM, et al. HITS: a short domestic violence screening tool for use in a family practice setting. Family Med Vol. 1998;30(7):508–12. [PubMed] [Google Scholar]
- 29.KESSLER RC, ANDREWS G, COLPE LJ, MROCZEK DK HIRIPIE, NORMAND S-LT, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med. 2002;32(6):959–76. [DOI] [PubMed] [Google Scholar]
- 30.Kamiab Z, Tavanaee K, Sepehran M. Prevalence of stunting and some related factors in 6-year-old children in Rafsanjan City in 2018: a cross-sectional study. JRUMS. 2020;19(9):941–54. [Google Scholar]
- 31.Huey SL, Finkelstein JL, Venkatramanan S, Udipi SA, Ghugre P, Thakker V, et al. Prevalence and correlates of undernutrition in young children living in urban slums of Mumbai, India: a cross-sectional study. Front Public Health. 2019;7:191. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Gebru NW, Tariku A, Abebe SM, Loha E, Woldie H. Double burden of malnutrition and associated factors among adolescent girls and boys in Ethiopia. Nutr J. 2021;20(1):10.33499878 [Google Scholar]
- 33.Dolatian M, Hesamy K, Zahiroddin A, Velaie N, Alavi Majd H. Evaluation of prevalence of domestic violence and its role on mental health. Pajoohandeh. 2012;16(6):277–83. [Google Scholar]
- 34.Nouhjah S, Latifi SM. Variation in the prevalence of domestic violence between neighboring areas. Int Sch Res Notices. 2014;2014:721951. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Kamali K, Maleki A, Yazdi SAB, The prevalence of violence and its association with mental health among the Iranian population in one year after the outbreak of COVID-19 disease. BMC Psychiatry 23, 33 (, Hajnasiri H, Ghanei Gheshlagh R, Sayehmiri K, Moafi F, Farajzadeh M et al. Domestic Violence Among Iranian Women: A Systematic Review and Meta-Analysis. Iran Red Crescent Med J. 2016;18(6): e34971. [DOI] [PMC free article] [PubMed]
- 36.Ghodsi D, Rasekhi H, Yari Z, Roustaee R, Nikooyeh B, Faramarzi A, et al. Prediction and analysis of trends in the nutritional status of children under 5 years in Iran: reanalysis of the results of national surveys conducted between 1998 and 2020. Front Nutr. 2023;10:1083318. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Ahmadi B, Alimohamadian M, Golestan B, Bagheri Yazdi A, Shojaeezadeh D. Effects of domestic violence on the mental health of married women in Tehran. J Sch Public Health Inst Public Health Res. 2006;4(2):35–44. [Google Scholar]
- 38.Amini L, Heidary M, Daneshparvar H, Sadeghi Avval Shahr H, Mehran A, Afshar B. Mental health and social function among women subjected to intimate partner violence: a cross-sectional study. Acta Med Iran. 2013;51(9):645–53. [Google Scholar]
- 39.Amini L, Heidary M, Daneshparvar H, Sadeghi Avval Shahr H, Mehran A, Afshar B. Mental health and social function among women subjected to intimate partner violence: a cross-sectional study. Acta Med Iran. 2013;51(9):645–653.
- 40.Devries KM, Mak JYT, Garcia-Moreno C, Petzold M, Child JC, Falder G, et al. The global prevalence of intimate partner violence against women. Science. 2013;340(6140):1527-8. [DOI] [PubMed]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.