
==== Front
BMC Public Health
BMC Public Health
BMC Public Health
1471-2458
BioMed Central London

39103845
19586
10.1186/s12889-024-19586-4
Research
Sex-specific compensatory model of suicidal ideation: a population-based study (Urban HEART-2)
Rashidi Fatemeh 12
Karimi Keyvan 23
Danandeh Khashayar 2
Ansari Abtin 12
Asadi-Lari Mohsen 4
Memari Amir Hossein memari_ah@tums.ac.ir

2
1 grid.411705.6 0000 0001 0166 0922 School of Medicine, Tehran University of Medical Science, Tehran, Iran
2 grid.411705.6 0000 0001 0166 0922 Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Science, Tehran, Iran
3 grid.411705.6 0000 0001 0166 0922 Department of Epidemiology, School of Public Health, Tehran University of Medical Science, Tehran, Iran
4 https://ror.org/03w04rv71 grid.411746.1 0000 0004 4911 7066 Department of Epidemiology, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
6 8 2024
6 8 2024
2024
24 212031 10 2023
25 7 2024
© The Author(s) 2024, corrected publication 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Introduction

Suicidal ideations (SI), also known as suicidal thoughts, refer to impulses, desires, and obsessions related to death. Prevalence of suicidal ideation was 14 percent. The current study assumed that identifying the true predictors of SI would allow for a greater understanding of suicide risk.

Methods

In this cross-sectional population-based study, 17,644 residents aged from 15 to 90 years were selected through a multi-stage sampling method from 22 districts of Tehran. Using hypothesized causal models, the pathways through which various variables influenced the components of SI were identified. Also, the applicability of the compensatory and risk-protective models of resiliency for the prediction of SI was tested by using the interaction multiple regression analyses.

Results

SI was experienced by 13.44% of the study population. SI was more prevalent with individuals between the ages of 15 to 24. There are no differences between men and women when covariate analysis is used. The significant predictions by anxiety and physical activity (moderate) indicate support for the compensatory model for male and female, while the significant prediction by those indicates support for the risk-protective model for females.

Conclusion

PA would both lessen the detrimental impact of anxiety on suicidal thoughts and potentially reduce the probability of SI. It's important to develop and evaluate PA-enhancing treatments, especially for woman who are experiencing anxiety.

Keywords

Suicidal ideation
Physical activity
Anxiety
issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
==== Body
pmcIntroduction

Suicidal ideations (SI), also known as suicidal thoughts or ideas, refer to a range of impulses, desires, and obsessions regarding death [1]. Suicide is the fourth leading cause of death among 15–29-year-olds [2] and each year more than 700,000 people (represents a global suicide rate of 9.0 (13.7 men, 5.4 women) per 100,000 population take their own lives globally [3]. In addition to that prevalence, six more persons are negatively impacted by suicide in significant psychological, social, and economic ways. According to the World Health Organization (WHO), someone attempts suicide every three seconds and commits suicide every forty seconds around the globe [4]. Suicide is a major issue affecting public health that accounts for 1% of the global disease burden [4] and has increased by 60% over the past 45 years [5]. Middle east and Africa regions are among the most attempted suicide rates. Iran is at the top of the suicide and suicide attempt rates among all the Middle Eastern countries with rates of 5.2 and 193.49 per 100,000 people respectively. Also, a history of chronic diseases such as mental health issues, low socioeconomic status, low grades of education, and drug addiction are the most important risk factors for suicidal attempts [6, 7].

A recently conducted systematic review in Iran showed the prevalence of suicide death was 8.14 and the prevalence of suicide attempts in the whole population was 131 (152 per 100,000 women and 128 per 100,000 men) per 100,000 people [8].

Since suicide can be prevented, WHO stated that conducting empirical research on suicide risk factors in order to identify particularly vulnerable individuals is of the utmost importance. Over the past few decades, numerous studies have investigated the associated risk factors and showed that SI is predictive of attempted and completed suicides [9–11]. Female gender, parental psychopathology, childhood family adversities, unemployment and prior history of suicidality can be considered as a predictor or risk factors for suicidal behaviors (i.e. suicidal ideation, plans and attempts) in both developed and developing countries [12].

Regarding adolescents, gender difference and adverse childhood experiences (e.g. physical and sexual abuse, bullying, parental neglect) can be considered as potential risk factors for SI in low- and middle-income countries [13].

In other hand despite 50 years of research, prediction accuracy for outcomes has only been slightly better than chance. No broad or subcategory reliably predicted outcomes, and studies rarely considered multiple risk factors [14].

Efforts have been made to identify interventions that effectively reduce SI risks. Although most of the interventional studies have been done in high-income countries with the USA and South Korea at the top, nearly 80% of the suicides in the world occurred in low/middle-income countries [15]. Also, especially walking and jogging are the two significant interventions that decrease the SI index in both genders. Yoga and strength training are the most effective for older and younger people respectively [16]. In a study conducted in the southwest of Iran among older adults, it was found that the prevalence of suicidal ideation is higher among women. However, this association does not remain significant when considering independent factors (it was significant in the crude model but not in the multivariate or adjusted model [17]. Nevertheless, the majority of studies have consistently noted that gender differences are associated with a female preponderance in suicidal ideation [18].

Regarding culturally unique suicidal strategies, one qualitative study attempted to identify themes based on cultural contexts in Iran. This study revealed five categories that explain suicide attempts, including personal factors and life experiences, family dynamics, social and educational influences, psychological-emotional problems, and stress coping strategies [19].

Prior research was inspired by medical understanding and frameworks, and thus focused primarily on medical diagnosis and treatment of depression [20]. Indeed, cognitive behavioral therapy and some antidepressants have been identified as effective interventions for depression. Protective factors include certain coping strategies (e.g., problem-focused coping and emotion-focused coping), [21] social support, and self-esteem [22]. Additionally, exercise or physical activity can act as a protective measure against suicidal thoughts and attempts. Kim et al. found that moderate physical activity, as per official guidelines [23], is negatively associated with SI [24]. The impact of exercise on reducing mental disorders such as depression and anxiety may also indirectly contribute to lower rates of suicidal behavior [25].

Previously risk factors such as social anxiety have been identified for suicide attempts in emerging adulthood [26]. Studies have shown significant negative correlations between all levels of PA and suicidal behavior among older people [27, 28]. Resiliency models proposed for assessing the relationships between risk and protective factors and adjustment can provide valuable insights into the protective role of PA in the relationship between mental health issues and suicidal ideation.

At least four generic resiliency models currently exist, including the compensatory model, the risk-protective model, the challenge model, and the protective-protective model [29–31]. According to the compensatory model, risk and protective factors have additive effects on maladjustment. According to the risk-protective paradigm, maladjustment is related to the interaction between risk and protective factors. Specifically, higher levels of the protective factor could mitigate the effect of risk factor on maladjustment [32].

Since suicidal ideation logically precedes suicidal acts, the current study assumed that identifying the true predictors (after adjusting by the pertinent variables) of suicidal ideation would allow for a greater understanding of suicide risk. The purpose of this study was to understand how anxiety and physical activity interact in predicting suicidal ideation in a large population that are likely applicable to the entire population of men and women across various age groups.

Methods

The studied sample was drawn from the Urban HEART project's second round. It developed by the WHO Centre for health development located in Kobe, Japan, may provide an example of efforts to reduce urban inequality. Urban HEART helps countries and districts to systemically producing evidence to evaluate and address to unfair health conditions and inequity in urban settings [33]. The Urban Health Equity Assessment and Response Tool (Urban HEART) project was a large population-based cross-sectional survey conducted in Tehran, Iran. In-home interviews were conducted with the respondents. Before collecting data, all interviewers attended a two-day training workshop [34].

Participants

Men and women over the age of 15 from the population of Tehran were included in the current study, with the final sample consisting of 17,644 individuals (54% being female) who correctly completed all questionnaire sections. Respondents were stratified and randomly selected (regardless of their professions) to test the questionnaire. The questionnaires were asked in an interview which took around 25 min within the household. If the respondent was illiterate or unable to self-administer the questionnaires, they were completed through an interview. The Urban HEART-2 cross-sectional survey was conducted in 22 districts of Tehran, Iran's capital city and includes 3,4700 households. Our study was approved by the Ethics Committee of Tehran University of Medical Sciences.

Urban HEART-2 (UH-2) based on response-oriented and assess the equity of health in Tehran city, which can demonstrate improved visions to decision-makers in health policy and lead to an improvement in community health. Six action areas were defined which included “physical environment and infrastructure”, “social and human development”, “economics”, “governance”, “cultural” and “health and nutrition”.

Data collection

Each of Tehran's 22 districts and 380 localities was classified as a stratum (with the exception of six neighborhoods that were inaccessible for security reasons and therefore excluded from the study). Because some of the respondents were illiterate, the interviewers completed the GHQ by reading the items audibly to all interviewees. For some subjects, repeated questioning was required to obtain an answer. Totally 34,700 families from 22 districts in Tehran were covered by this population-based survey [35] and more than 22,500 participants responded to our health questionnaire (rate = 65%). After removing records with missing and invalid data from 22,500 initial health-related datasets, 17,644 participants remained for data analyses (rate = 78%) Fig. 1. (Study sample).Fig. 1 Study sample

Variables

In the demographic section of the questionnaire, participants reported their age, relationship status, highest education level achieved, occupation, and number of family members.

Socio-demographic variables

Age of participant were categorized in three group; 15–29 years “young adult”, 30–60 years “adults” and over 60 years as elderly people. Marital status was defined in three categories namely; never married, married and previously married (divorced/widow). The education of responders was categorized in three levels; illiterate/primary education, secondary education and diploma and higher education. Occupation status in this study was defined in three subgroups including; employed, unemployed and retired. The economy level was defined as sufficiency of family’s income to support their life costs and categorized in low, middle and high levels. Chronic illnesses in the family include diabetes, cancer, myocardial infarction, stroke, asthma, hypertension, and osteoporosis.

The participants were requested to provide information regarding the number of family members living in their household or a total number of family members, in order to determine the size of their family. The coding scheme assigns a value of 1 to indicate a small family with 1 to 3 members, a value of 2 to represent a medium family consisting of 4 or 5 individuals, a value of 3 for a large family comprising6 or 7 individuals, and a value of 4 indicating a very large family size consisting of 8 or more individuals [36].

GHQ-28

In community and non-psychiatric clinical settings, the General Health Questionnaire (GHQ) is the most commonly used screening instrument for detecting psychiatric disorders [37]. In the present study, the available Farsi version of the GHQ-28 was used [38]. A review of studies on the validity of the GHQ–28 in various countries, including Iran, demonstrates its high validity and reliability as a community screening instrument for mental disorders [39]. Four 7-item subscales are: somatic symptoms, anxiety and insomnia, social dysfunction, and severe depression. It permits the evaluation of mental health on four dimensions corresponding to these four scales. Regardless of version type, the structure of every query is always identical. To derive scale scores with more variability, we used Likert scoring (0123) instead of the original scoring procedure (0011) [40].

Suicidal ideation

Suicidal ideation was assessed on the basis of responses to 4 questions contained in the 28-item GHQ [37]. The subjects were instructed to respond to queries about how they had felt "over the past few weeks" as per standard GHQ protocol. Responses of “not at all”, “no more than usual’, “rather more than usual” or “much more than usual” were recorded for 2 questions: “Have you recently felt that life is not worth living?”, and “Have you recently found yourself wishing you were dead and away from it all?”. Similarly, responses of “definitely not”, “I don’t think so”, “has crossed my mind” or “definitely has” were recorded for the other 2 questions: “Have you recently had thoughts of the possibility that you might do away with yourself?”, and “Have you recently found the idea of taking your own life kept coming into your mind?” A binary scoring method was used that negative response; “not at all”, “no more than usual”, “definitely not” and “I don’t think so” given 0 score and 1 score was assigned to other options (positive response) [41]. By adding the binary scores for each of the 4 questions, giving a score from 0 to 4, a scale of suicidal ideation can be devised, and this can be used to compare subjects’ responses with other instruments employed. Thus the degree of suicidal ideation can be related to measures of hopelessness [42] self-esteem [43] anomie [44] depressive affect [43] and locus of control [45] as well as the subscales of the GHQ [46].

Anxiety

The Likert scoring method, ranging from 0 to 7, was employed to assess levels of anxiety within the subdomain of the GHQ-28. This approach allowed for the determination of anxiety scores, ranging from minimum to severe. Total sum scores were created for anxiety (7 items 8–14). Responses of “not at all”, “no more than usual’, “rather more than usual” or “much more than usual” were recorded for 7 questions: “lost much sleep over worry?”, “had difficulty in staying asleep more once you are off?”, “felt constantly under strain?”, “been getting edgy and bad-tempered?”, “been getting scared or panicky for no good reason?”, “found everything getting on top of you?”, and “been feeling nervous and strung-up all the time?”.

Physical activity

GPAQ

To measure physical activity, we utilized consumption of energy Metabolic Equivalents (MET)-min/week and physical activity level (low, moderate, and high) [47]. The following categories of physical activity are defined in terms of MET-mins per week:

High level: vigorous-intensity activity in at least 3 days with a consumption of at least 1500 MET-min/week or a combination of walking and moderate or vigorous-intensity activities in at least 7 days with a consumption of at least 3000 MET-min/week. Moderate level: vigorous-intensity activity for at least 20 min in 3 or more days moderate-intensity activity or walking for at least 30 min in 5 or more days or a combination of walking and moderate or vigorous-intensity activity in at least 5 days with a consumption of at least 600 MET-min/week. Low level: not meeting the criteria for either high or moderate level [48].

GPAQ

Physical activity variables were derived from a valid and reliable Persian version [47, 49] of the Global Physical Activity Questionnaire (GPAQ- version 2) [48] developed by WHO, which has demonstrated high validity and reliability for assessing physical activity in a national surveillance in middle-income developing countries [50].

Statistical analysis

Data preprocessing and analysis for this study were conducted using Stata version 17. Following the rectification of unusual and missing data, categorical variables were characterized using frequency and percentage measures. The examination of SI patterns entailed tabulation, employing a Chi-squared test to explore associations at the socio-demographic level in men and women separately. To ascertain the linkage between socio-demographic factors, physical activity level, anxiety, domestic violence, tabaco use (as covariates) and SI, a two-step logistic regression analysis was executed. Initially, a univariable logistic regression was carried out over gender subgroups. Subsequently, employing the forward method, a multivariable logistic regression analysis was performed to evaluate the adjusted impact of each factor on SI within the study cohort. The independent variables considered encompassed age, gender, marital status, family size, occupation, housing situation, economic status, family tobacco use, family addiction, family violence, anxiety, and physical activity. SI was considered as a Primary outcome in this study. A confidence interval of 95% was applied, and statistical significance was determined at a threshold of p < 0.05.

The compensatory and risk-protective models were evaluated using the previously proposed multiple regression techniques [30, 32]. Each model was evaluated separately for men and women. In the same analysis, the compensatory and risk-protective models were evaluated by regressing the outcome measure (suicidal ideation) on the risk factor (anxiety), the relevant protective factor (moderate PA), risk factor × protective factor. Significant prediction by both the risk and protective factors indicates support for the compensatory model.

PA was determined as a quantitative variable with low was 1 and moderate was 2 and excluded high levels. Anxiety was determined as an ordinal variable. Interaction multiple regressions was tested. The compensatory model would suggest that anxiety will contribute positively, while PA will contribute negatively to the prediction of suicidal ideation [51, 52].

Results

A total of 17,644 individuals participated in the study, with 46% (8133) being male and 9515 being females. The age spectrum of participants spanned from 15 to 90 years, with the majority falling within the 25 to 34-year bracket. Among the male participants, 73% were married, 20% were unemployed, and 44% reported a middle-income level. In the female participants most of them being married, and reported low economy level (46%) with unemployment status (85%). The educational distribution revealed that a significant proportion possessed secondary education (53% in males and 58% in females). When considering aspects related to mental health and its determinants, suicidal ideation (SI) was reported by 12.53% of the men and 14.23% of women. Additionally, anxiety symptoms were disclosed by 31.95% and 38.43% of the men and women, respectively. Descriptive socio-demographic and other pertinent characteristics of the study participants are outlined in Table 1. Table 1 The related characteristic of study population by SI in gender subgroup

Variables	Category	Men (n = 8133)	Women (n = 9511)	
With SI %	Without
SI%	P value	Total (n)	With SI%	Without
SI%	P value	Total (n)	
Age	15 -29	16.8	83.2	< 0.001	975	19.7	80.3	< 0.001	1066	
30 -60	12.8	87.2	4256	13.2	86.8	6245	
60 > 	10.7	89.3	2902	14.5	85.5	2200	
Marital status	Married	11.1	88.9	< 0.001	5920	12.6	87.4	< 0.001	7021	
Never married	16.2	83.8	1830	18.5	81.5	1263	
Previously married	17.2	82.8	383	18.7	81.3	1227	
Education	Illiterate/primary	13.1	86.9	< 0.001	1246	16	84	< 0.001	1777	
Secondary	13.6	86.4	4337	14.8	85.2	5541	
Higher	10.3	89.7	2528	11.2	88.2	2155	
Job status	Unemployed	17.9	82.1	< 0.001	1672	14.3	85.7	0.55	8062	
Employed	11.6	88.4	4242	14.3	85.7	763	
Retired	10.2	89.8	2219	12.8	87.2	686	
Family size	Small	16.6	83.4	0.002	307	18	82	< 0.001	477	
Medium	11.9	88.1	3682	13.1	86.9	4183	
Large	12.3	87.7	3567	14.1	85.9	4259	
Very large	16.8	83.2	507	20.5	79.5	528	
Economy	Low	15.3	84.7	< 0.001	3771	17.6	82.4	< 0.001	4446	
Middle	10.5	89.5	3571	11.6	88.4		4298	
High	8.9	91.1	721	9.7	90.3		703	
PA-level	low	12.4	87.6	0.004	4489	14.5	85.5	0.03	5933	
moderate	10.8	89.2	1840	12.7	87.3	2236	
high	14.5	85.5	1804	15.4	84.6	1342	
Tabaco use	Yes	16.4	83.6	< 0.001	2064	19.7	80.3	< 0.001	2171	
No	11.2	88.8	6069	12.6	87.4	7340	
Anxiety	Yes	30.5	69.5	< 0.001	2486	31.1	68.9	< 0.001	3500	
No	3.8	96.2	5294	3.5	96.5	5607	
Domestic Violence	Yes	22.4	77.6	< 0.001	673	27.6	72.4	< 0.001	976	
No	11.6	88.4	7443	12.7	87.3	8507	

Each of the variables detailed in Table 1 exhibited a substantial association with the prevalence of suicidal ideation (SI) both in men and women. For instance, individuals aged 15 to 29 demonstrated the highest SI prevalence in contrast to other age cohorts (p < 0.001). Similarly, individuals who were previously married or never married, those with lower familial income, limited engagement in PA, those exposed to familial violence and tobacco use, as well as individuals experiencing anxiety, exhibited a direct positive relationship with SI prevalence within the population of men and women. Domestic violence and tabaco use were more related with SI prevalence in women compared to men (27.6% and 19.7% vs. 22.4 and 16.4).

Table 2 Univariable Logistic regression of SI prevalence by related factors in men and women

Variables	Men	Women	
ORa (95%CIb)	P value	OR (95% CI)	P value	
Age, year	
 > 60	Reference		Reference		
 30–60	1.21 (1.04 -1.40)	0.01	0.89 (0.77–1.03)	0.31	
 15 -29	1.67 (1.36–2.04)	< 0.001	1.44 (1.19 -1.75)	< 0.001	
Marital status	
 Married	Reference		Reference		
 Never married	1.55 (1.34 -1.80)	< 0.001	1.56 (1.33 -1.83)	< 0.001	
 Previously married	1.67 (1.26 -2.20)	< 0.001	1.59 (1.35 -1.86)	< 0.001	
Job-status	
 Retired	Reference		Reference		
 Unemployed	1.91 (1.51–2.31)	< 0.001	1.13 (0.90 -1.43)	0.27	
 Employed	1.15 (0.97 -1.35)	0.09	1.13 (0.83 -1.53)	0.41	
Education level	
 Diploma and Higher	Reference		Reference		
 Secondary education	1.37 (1.17 -1.60)	< 0.001	1.38(1.18 -1.61)	< 0.001	
 Illiterate /primary	1.30 (1.10 -1.61)	0.01	1.51 (1.25 -1.81)	< 0.001	
Family size	
 Medium (normal)	Reference		Reference		
 Small	1.47 (1.07 -2.03)	0.02	1.45 (1.18 -1.85)	0.003	
 Large	1.07 (0.90- 1.20)	0.54	1.08 (0.96- 1.23)	0.18	
 Very large	1.49 (1.16 -1.92)	0.002	1.70 (1.35- 2.14)	< 0.001	
Economy	
 High	Reference		Reference		
 Middle	1.20 (0.90 -1.58)	0.19	1.23 (0.93- 1.53)	0.13	
 Low	1.85 (1.41 -2.42)	< 0.001	1.99 (1.53- 2.59)	< 0.001	
 Tabaco use (yes/no)c	1.55 (1.35 – 1.79)	< 0.001	1.69 (1.49 – 1.92)	< 0.001	
Physical activity level	
 Low	Reference		Reference		
 Moderate	0.85 (0.71- 0.97)	0.04	0.85 (0.73 -0.98)	0.02	
 High	1.18 (0.96 -1.39)	0.06	1.07 (0.90 – 1.26)	0.41	
 Anxiety (yes/no)c	11 (9.33 – 12.96)	< 0.001	12.41 (10.59 -14.56)	< 0.001	
 Domestic violence (yes/no)c	2.19 (1.80 -2.66)	< 0.001	2.62 (2.24 – 3.06)	< 0.001	
aodds Raio, bconfidence interval, c” yes” groups compared to “no” groups

These associations are visually depicted in Fig. 2, which illustrates the intricate patterns of SI prevalence across subgroups defined by age, education, family-size, and economy level.Fig. 2 Prevalence (%) of SI by related factors (age_cat, education, economy and family_size) in males and females

The outcomes of univariable and multivariable sex-specific logistic regression analyses are provided in Table 2 and Table 3. Within age categories, men aged 15 to 29 years exhibited a1.6-fold increased odds of experiencing SI in comparison to those older than 60 years (OR = 1.67, p < 0.001). Also, for women this association were declarable (OR = 1.44, p < 0.001). This association remained statistically significant only in women after accounting for other covariates within the model (OR = 1.68, p < 0.001). Conversely, no significant probability of SI was discerned among the remaining age groups relative to the reference group of individuals older than 60 years in the adjusted model both in men and women. Table 3 Multivariable logistic regression of SI prevalence by related factors in men and women

Variables	Men	Women	
ORa (95%CIb)	P value	OR (95% CI)	P value	
Age, year	
 > 60	Reference		Reference		
 30–60	1.27 (0.90 -1.79)	0.17	1.06 (0.88–1.23)	0.50	
 15 -29	1.18 (0.95–1.47)	0.12	1.68 (1.27 -1.22)	< 0.001	
Marital status	
 Married	Reference		Reference		
 Never married	1.27 (1–1.80)	0.05	1.51 (1.21 -1.90)	< 0.001	
 Previously married	1.19 (0.82–1.71)	0.34	1.48 (1.17 -1.86)	0.001	
Job status	
 Retired	Reference		Reference		
 Unemployed	1.48 (1.13–2.92)	0.003	1.20 (0.89 -1.63)	0.20	
 Employed	1.04 (0.82 -1.31)	0.71	1.15 (0.79 -1.68)	0.43	
Family size	
 Medium (normal)	Reference		Reference		
 Small	1.50 (1.24 -2.23)	0.03	1.21 (0.86 -1.65)	0.25	
 Large	0.95 (0.80- 1.11)	0.53	1.03 (0.89- 1.19)	0.67	
 Very large	1.04 (0.79 -1.42)	0.67	1.37 (1.06- 1.80)	0.02	
Economy	
 High	Reference		Reference		
 Middle	1.05 (0.77 -1.44)	0.19	1.23 (0.93- 1.53)	0.13	
 Low	1.33 (1.08 -1.81)	0.04	1.99 (1.53- 2.59)	< 0.001	
 Tabaco use (yes/no)c	1.22 (1.10 – 1.44)	0.01	1.40 (1.21 – 1.62)	< 0.001	
Physical activity level	
 Low	Reference	Reference	
 Moderate	0.80 (0.66- 0.96)	0.03	0.85 (0.73 -0.98)	0.02	
 High	1.02 (0.85 -1.23)	0.77	1.07 (0.90 – 1.26)	0.41	
 Anxiety (yes/no)c	10.63 (8.98 – 12.59)	 < 0.001	11.57 (10.59 -14.56)	< 0.001	
 Domestic violence (yes/no)c	1.47 (1.17 -1.88)	0.001	1.87 (1.57 – 2.24)	< 0.001	
aOdds Raio, bconfidence interval, c” yes” groups compared to “no” groups

Individuals classified as previously married or never married exhibited an elevated Odds of SI in both gender in crude model but in the multivariable model only women shown this relationship in terms of marital status and SI (OR = 1.50, p < 0.001). Notably, a small and very large family size demonstrated a positive association with SI prevalence when compared to medium family sizes in univariable analysis. But in the adjusted model only women in very large family had more Odds of SI compared to those who in the medium family size (OR = 1.37, p = 0.02). Furthermore, unemployment emerged as a factor associated with an increased odds of SI in men but not in women, with an average elevation of 1.37 times compared to retired individuals, even after adjusting for other pertinent variables (OR = 1.37, p = 0.006). Among the observed associations, one of the most robust was between SI and anxiety (OR = 10.43, p < 0.001 in men and OR = 11.57, p < 0.001 in women). Despite the positive relationship between factors such as; family economy, tobacco use, domestic violence, and SI within the adjusted model in both gender groups, a contrasting effect was apparent for moderate levels of physical activity (PA). Compared to the category of low activity, moderate PA exhibited a protective influence on SI (OR = 0.80, p = 0.003 in men and OR = 0.85, p = 0.02 in women).

The results of the analysis for testing the compensatory and risk- protective models in which Physical activity served as the protective factor (Table 4). The nonsignificant predictions of PA failed to support the compensatory model for males (OR = 1.65; CI 95% [1.63–1.75]). The significant prediction by anxiety × PA (moderate) indicates a support for the risk-protective model for males. This risk protective model shows that the odds of suicidal ideation decreased by an average of 27% for each unit increase in PA. Table 4 Results of testing the compensatory model and risk-protective model to predict SI prevalence for males

Variable	OR	Z	95%CI	
Lower bound	Upper bound	
Anxiety (risk factor)	1.65	28.3**	1.63	1.75	
Physical activity (protective factor)a	.84	-1.83	.70	1.01	
Anxiety × Physical activity	1.38	24.87**	1.35	1.42	
aMaderate physical activity vs. low physical activity

* P-value < .05 **P-value < .001

Table 5 showed that the results of the analysis for testing the compensatory and risk-protective models in females, which Physical activity served as the protective factor for females. The significant predictions by both anxiety and PA (moderate) indicate support for the compensatory model, while the significant prediction by anxiety × PA (moderate) indicates support for the risk-protective model for females. Furthermore, Figs. 3 and 4 show the anxiety × PA interaction effect on SI in the males and females respectively. Table 5 Results of testing the compensatory model and risk-protective model to predict SI prevalence for females

Variable	OR	Z	95%CI	
Lower bound	Upper bound	
Anxiety (risk factor)	1.73	34.78**	1.68	1.79	
Physical activity (protective factor)a	.83	-2.37*	.72	.96	
Anxiety × Physical activity	1.39	30.38**	1.36	1.42	
aMaderate physical activity vs. low physical activity

*P-value < .05 **P-value < .001

Fig. 3 Suicidal ideation as a function of anxiety × PA for males

Fig. 4 Anxiety and PA interaction effect on SI in females

Discussion

To our knowledge, there is little information on the relationship between SI and its protective or risk variables (risk factors: being unemployed, having a history of family addiction, experiencing familial violence, and belonging to a larger family size and protective factors decrease the likelihood of experiencing SI or mitigate the impact of risk factors (like moderate PA and having a moderate family size)) in a large sample of individuals with suicidal ideation, as well as the application of two resilience models to SI (how risk and protective factors interact to influence SI). As we mentioned before resilience models such as compensatory and risk-protective. Compensatory model suggests the presence of protective factors can directly reduce the impact of risk factors, leading to better outcomes. For example, engaging in moderate PA can independently lower the likelihood of SI. Risk-Protective model proposes higher levels of protective factors can decrease the negative effects of risk factors.

We are reporting a 13.44% prevalence of SI in the study population. This result underscores the multifaceted nature of SI, indicating that its prevalence is influenced by various significant demographic variables such as age, gender, and family size. A population-based study of 82 countries found a similar overall pooled prevalence of SI at 14.0%. These findings emphasize the need to consider diverse demographic and lifestyle factors to better understand the prevalence of SI. There was significant regional variation in the prevalence of mental health problems. The highest pooled prevalence of suicidal ideation was observed in the Africa Region (21.0%) and the lowest was in the Asia region with 8.0% [53].

Being unemployment emerged as a significant factor associated with increased odds of SI, even after adjusting for other variables. Individuals classified as previously married or never married exhibited an elevated risk of SI in both unadjusted and adjusted models. Interestingly, moderate family size appeared to have a protective effect on SI prevalence when compared to larger family sizes. Furthermore, familial tobacco use, family addiction history, and familial violence showed positive relationships with SI in the adjusted model. Addressing emotional needs relates to the fulfillment that comes from connecting or reconnecting with the individual’s family, friends, and the relationships they have with others and with themselves [54, 55].

Individuals aged 15 to 24 demonstrated an increasing likelihood of experiencing SI for both genders compared to those older than 65 years, even after adjusting for potential confounders. Despite young women potentially facing different challenges than young men, such as societal pressures, gender-based discrimination, and varied coping mechanisms that may influence the prevalence and intensity of suicidal ideation differently, [56–58].

Our results indicate that the likelihood of SI in the 15–29 age group is higher for men than for women (1.67 vs. 1.44). However, both genders show significantly elevated likelihood compared to the reference group which was aligned with the study of Kerr et. Al that indicated boys and men (Ages 9 to 29 Years) were at high risk of SI [59]. Conversely, no significant probability of SI was found among other age groups relative to the reference group of older individuals. Adolescence is a developmental stage associated with an increased risk for the onset and growth of suicidal thoughts and behaviors [60]. In fact, it has been documented that the lifetime prevalence of SI among adolescents is 12.1% [61]. In light of the fact that suicidal ideation is a strong predictor of suicide attempts and completed suicide, it is crucial to develop models of vulnerability and protection against suicidal ideation among young adolescents in order to implement early prevention and intervention programs [62].

These risk factors are multifactorial, intricate, and interrelated. Most are connected to their families and schools. The significance of adequate parental regulation including supervision, monitoring, rule-setting, and other forms of behavioral control is one of the most well-documented findings from research on adolescents and their families [63, 64]. The risk factors associated with adolescent suicide behavior are multifactorial. Most are related to the family and the school. The importance of adequate parental regulation involving supervision, monitoring, rule-setting, and other forms of behavioral control is documented in [63, 64]. Parental bonding and a sense of family connection are also associated with lower levels of depression, and SI [65]. As we presented having a family with moderate size appeared to be a protector and family addiction history, and familial violence showed positive relationships with SI.

While initially, women displayed a higher likelihood of SI than men, this difference disappeared when accounting for covariates. Previous research has indicated that the effects of social risk and protective factors are modified by gender [66–68]. For women and men, it was evident that the risk-protective model was supported when PA (moderate) was the protective factor. These results suggest that a moderate level of PA reduces the effects of anxiety on suicidal ideation among men and women. For women only, results regarding PA also supported the compensatory model. This result suggests that for women, the strength of the association between suicidal ideation and anxiety is reduced when PA is considered. Previous data led to inconsistent findings with regards to the impact of gender on suicidal ideation. The potential explanation for these findings could be attributed to the difference in ways to cope performed by individuals of different genders [69]. In a study conducted among 15–25 year olds in Malaysia, it was shown that suicidal thoughts are more common in men than women and also age can be a predictive factor in men [70]. Suicide rates were higher among men compared to women [71]. However, suicide attempts were most prevalent among young women, closely followed by young men [72].

It has been found that elderly males are at higher risk for suicide than any other group [73]. Although elderly women make more attempts, elderly men complete suicides more often [11]. A systematic review of suicidal behavior in Europe and America has concluded that suicidal ideation and behavior are more common among women [74]. There is an inconsistency between the pieces of literature. In China, the prevalence of SI was substantially higher among men, whereas the converse was in India for older individuals [27]. Consequently, the principal finding highlights the need for context-based interventions. Considering that individuals with moderate PA had a lower association with SI than those with low PA, strategies such as encouraging regular PA and improving walkability should be considered.

The results highlighted that moderate PA level was associated with a protective effect on SI in comparison to low levels of physical activity. The significance of low physical health as a risk factor appears to be well-established [75]. Although an investigation examined the risk and protective factors for SI from childhood to adulthood on mental and physical health PA had no significant effect [76]. With reference to suicidality, the factors that modulate or serve as buffers against taking one’s own life are referred to as protective factors [77]. Despite increasing support for protective factors in suicide prevention the positive message of recovery from suicidal ideation and the hope this may engender for suicidal clients has garnered little attention [78]. It has been shown that being physically active, even in moderate form, can enhance life satisfaction and elevate people’s level of happiness [79].

The study among Korean adolescents demonstrate that physical activity does not have the protective impact that is generally believed to shield adolescents from suicidal behaviors. Adolescents in Korea are more prone to attempt suicide if they engage in frequent, intense physical activity [80]. Addressing physical needs includes promoting a healthy lifestyle and generating interest in previously enjoyable hobbies or pastimes as a means of consolidating internal coping strategies [81, 82]. Perhaps physical activity can be considered as a coping skill and people can benefit from its effect in stressful situations throughout the day [83]. Therefore, it can be said that physical activity is effective in improving mental health by improving the level of mood and as a coping skill, and reduces anxiety symptoms, which are one of the risk factors of suicidal thoughts.

The most robust associations were observed between SI and anxiety in this study. Several national organizations have identified anxiety and its associated disorders as significant risk factors for suicide [84, 85]. Once an individual's suicidal thoughts get activated, feelings of anxiety and agitation may manifest as a way to focus their attention on suicide. This interaction between attentional fixation on suicide and a sense of hopelessness might contribute to an increased risk of suicide [86, 87]. Despite some early research suggesting that there is no association between anxiety disorders and suicidality [88, 89]. Adolescents who attempt suicide, compared to those who experience suicidal ideation, are more likely to have been diagnosed with anxiety disorders [90]. In general, there is a notable correlation between anxiety and its associated issues, and the possibility of experiencing suicidal thoughts and engaging in suicide attempts. These connections have been found to be statistically significant in prospective studies [91].

Limitations.

It is important to acknowledge the study's limitations. Due to the study's use of correlation analysis on concurrently collected data, it is not possible to infer a causal connection between variables. All data in this investigation were collected via self-report from the same source. Second, those who declined to take part in the study may have been more likely to have suicidal ideas and depressive symptoms. Third, the current study examined suicidal ideation as an adjustment factor (used it to control and understand its impact on other variables in our study, but this focus limits the applicability of our results to just those with suicidal thoughts, not those who have taken more severe actions), rather than suicide attempts or completions. Although suicidal ideation is a predictor of suicide attempts and completions [11], it is essential to recognize that suicidal ideation does not lead to suicide in the majority of people. Therefore, we need to take caution when projecting the results of this study to individuals who have attempted or completed suicide.

Conclusion

Overall, our research revealed a SI prevalence of 13.44%, which is in line with worldwide data. We demonstrated that PA would both lessen the detrimental impact of anxiety on suicidal thoughts and potentially reduce the probability of SI. It's important to develop and evaluate PA-enhancing treatments, particularly for those who are experiencing anxiety especially for woman.

Acknowledgements

None.

Authors’ contributions

F.R. wrote the main manuscript text and contributed in the developing idea. KH.D. and A.A contributed in the searching, extraction and drafting of the manuscript. K.K contributed in analysis. M.A contributed in data collection. A.H.M contributed in the developing idea and editing and revising manuscript. All authors reviewed the manuscript.

Funding

No funding was received for this study.

Availability of data and materials

The datasets analysed during the current study are not publicly available but will be accessible from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

Ethical approval was sought from the relevant council in Municipality of Tehran and Ethics Committee of Iran University of Medical Sciences (IUMS) in November 2010 for the survey. Our study was approved by the Ethics Committee of Tehran University of Medical Sciences. (IR.TUMS.NI.REC.1401.041). The aims of the survey were described to the participants, they were able to withdraw at any time during the interview and informed consent from all subjects or their legal guardians have been obtained. Interviews were scheduled to suit the respondents and they were assured that their information would be kept confidential.

Consent for publication

This study was conducted based on the Urban HEART-2 project which has been approved by the institutional review board of Iran University of Medical University.

Competing interests

The authors declared no competing interest.

This article has been updated to correct the missing figure 4.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Change history

9/2/2024

A Correction to this paper has been published: 10.1186/s12889-024-19808-9
==== Refs
References

1. Bernert RA Hom MA Roberts LW A review of multidisciplinary clinical practice guidelines in suicide prevention: toward an emerging standard in suicide risk assessment and management, training and practice Acad Psychiatry 2014 38 585 592 10.1007/s40596-014-0180-1 25142247
Bernert RA, Hom MA, Roberts LW. A review of multidisciplinary clinical practice guidelines in suicide prevention: toward an emerging standard in suicide risk assessment and management, training and practice. Acad Psychiatry. 2014;38:585–92. 25142247
2. https://www.who.int/news-room/fact-sheets/detail/suicide.
3. Organization WH. Suicide worldwide in 2019: global health estimates. 2021.
4. Bitew H, Andargie G, Tadesse A, Belete A, Fekadu W, Mekonen T. Suicidal Ideation, Attempt, and Determining Factors among HIV/AIDS Patients, Ethiopia. Depress Res Treat. 2016;2016:8913160.
5. Guo B, Harstall C. For which strategies of suicide prevention is there evidence of effectiveness? Copenhagen: World Health Organization. Regional Office for Europe; 2004;2004–07.
6. https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-021-11527-9.
7. https://cegh.net/article/S2213-3984(18)30252-5/fulltext.
8. Asadiyun M Daliri S Suicide attempt and suicide death in Iran: a systematic review and meta-analysis study Iran J Psychiatry 2023 18 2 191 37383956
Asadiyun M, Daliri S. Suicide attempt and suicide death in Iran: a systematic review and meta-analysis study. Iran J Psychiatry. 2023;18(2):191. 37383956
9. https://www.who.int/news-room/fact-sheets/detail/mental-health-strengthening-our-response/?gclid=CjwKCAjwg4SpBhAKEiwAdyLwvEN0wYV3unegWuVd6784Nt49o-U7KIQUH5VdX8LFF2ATOZFR9wgWLhoCIPUQAvD_BwE.
10. Large M Myles N Myles H Corderoy A Weiser M Davidson M Suicide risk assessment among psychiatric inpatients: a systematic review and meta-analysis of high-risk categories Psychol Med 2018 48 7 1119 1127 10.1017/S0033291717002537 28874218
Large M, Myles N, Myles H, Corderoy A, Weiser M, Davidson M, et al. Suicide risk assessment among psychiatric inpatients: a systematic review and meta-analysis of high-risk categories. Psychol Med. 2018;48(7):1119–27. 28874218
11. Mireault M de Man AF Suicidal ideation among the elderly: Personal variables, stress and social support Soc Behav Personal Int J 1996 24 4 385 392 10.2224/sbp.1996.24.4.385
Mireault M, de Man AF. Suicidal ideation among the elderly: Personal variables, stress and social support. Soc Behav Personal Int J. 1996;24(4):385–92.
12. Borges G Nock MK Abad JMH Hwang I Sampson NA Alonso J Twelve-month prevalence of and risk factors for suicide attempts in the World Health Organization World Mental Health Surveys J Clin Psychiatry 2010 71 12 21777 10.4088/JCP.08m04967blu
Borges G, Nock MK, Abad JMH, Hwang I, Sampson NA, Alonso J, et al. Twelve-month prevalence of and risk factors for suicide attempts in the World Health Organization World Mental Health Surveys. J Clin Psychiatry. 2010;71(12):21777.
13. McKinnon B Gariépy G Sentenac M Elgar FJ Adolescent suicidal behaviours in 32 low-and middle-income countries Bull World Health Organ 2016 94 5 340 10.2471/BLT.15.163295 27147764
McKinnon B, Gariépy G, Sentenac M, Elgar FJ. Adolescent suicidal behaviours in 32 low-and middle-income countries. Bull World Health Organ. 2016;94(5):340. 27147764
14. Franklin JC Ribeiro JD Fox KR Bentley KH Kleiman EM Huang X Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research Psychol Bull 2017 143 2 187 10.1037/bul0000084 27841450
Franklin JC, Ribeiro JD, Fox KR, Bentley KH, Kleiman EM, Huang X, et al. Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychol Bull. 2017;143(2):187. 27841450
15. Vancampfort D Hallgren M Firth J Rosenbaum S Schuch FB Mugisha J Physical activity and suicidal ideation: A systematic review and meta-analysis J Affect Disord 2018 225 438 448 10.1016/j.jad.2017.08.070 28858658
Vancampfort D, Hallgren M, Firth J, Rosenbaum S, Schuch FB, Mugisha J, et al. Physical activity and suicidal ideation: A systematic review and meta-analysis. J Affect Disord. 2018;225:438–48. 28858658
16. https://www.bmj.com/content/384/bmj-2023-075847.
17. Shiraly R Mahdaviazad H Zohrabi R Griffiths MD Suicidal ideation and its related factors among older adults: a population-based study in Southwestern Iran BMC Geriatr 2022 22 1 371 10.1186/s12877-022-03049-9 35484508
Shiraly R, Mahdaviazad H, Zohrabi R, Griffiths MD. Suicidal ideation and its related factors among older adults: a population-based study in Southwestern Iran. BMC Geriatr. 2022;22(1):371. 35484508
18. Lu L Xu L Luan X Sun L Li J Qin W Gender difference in suicidal ideation and related factors among rural elderly: a cross-sectional study in Shandong China Annals of general psychiatry 2020 19 1 9
Lu L, Xu L, Luan X, Sun L, Li J, Qin W, et al. Gender difference in suicidal ideation and related factors among rural elderly: a cross-sectional study in Shandong. China Annals of general psychiatry. 2020;19:1–9.
19. Bazrafshan MR Sharif F Molazem Z Mani A Cultural concepts and themes of suicidal attempt among Iranian adolescents Int J High Risk Behav Addict 2015 4 1 e22589 10.5812/ijhrba.22589 25883919
Bazrafshan MR, Sharif F, Molazem Z, Mani A. Cultural concepts and themes of suicidal attempt among Iranian adolescents. Int J High Risk Behav Addict. 2015;4(1): e22589. 25883919
20. Deuter K Procter N Evans D Jaworski K Suicide in older people: revisioning new approaches Int J Ment Health Nurs 2016 25 2 144 150 10.1111/inm.12182 26762697
Deuter K, Procter N, Evans D, Jaworski K. Suicide in older people: revisioning new approaches. Int J Ment Health Nurs. 2016;25(2):144–50. 26762697
21. Marty MA Segal DL Coolidge FL Relationships among dispositional coping strategies, suicidal ideation, and protective factors against suicide in older adults Aging Ment Health 2010 14 8 1015 1023 10.1080/13607863.2010.501068 21069608
Marty MA, Segal DL, Coolidge FL. Relationships among dispositional coping strategies, suicidal ideation, and protective factors against suicide in older adults. Aging Ment Health. 2010;14(8):1015–23. 21069608
22. Primananda M Keliat BA Risk and protective factors of suicidal ideation in adolescents Comprehensive child and adolescent nursing 2019 42 sup1 179 188 10.1080/24694193.2019.1578439 31192739
Primananda M, Keliat BA. Risk and protective factors of suicidal ideation in adolescents. Comprehensive child and adolescent nursing. 2019;42(sup1):179–88. 31192739
23. Craig CL Marshall AL Sjöström M Bauman AE Booth ML Ainsworth BE International physical activity questionnaire: 12-country reliability and validity Med Sci Sports Exerc 2003 35 8 1381 1395 10.1249/01.MSS.0000078924.61453.FB 12900694
Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381–95. 12900694
24. Kim H-W Shin C Han K-M Han C Effect of physical activity on suicidal ideation differs by gender and activity level J Affect Disord 2019 257 116 122 10.1016/j.jad.2019.07.043 31301611
Kim H-W, Shin C, Han K-M, Han C. Effect of physical activity on suicidal ideation differs by gender and activity level. J Affect Disord. 2019;257:116–22. 31301611
25. Mikkelsen K Stojanovska L Polenakovic M Bosevski M Apostolopoulos V Exercise and mental health Maturitas 2017 106 48 56 10.1016/j.maturitas.2017.09.003 29150166
Mikkelsen K, Stojanovska L, Polenakovic M, Bosevski M, Apostolopoulos V. Exercise and mental health. Maturitas. 2017;106:48–56. 29150166
26. Pereira AS Willhelm AR Koller SH Almeida RMMd Risk and protective factors for suicide attempt in emerging adulthood Ciencia & saude coletiva. 2018 23 3767 77 10.1590/1413-812320182311.29112016 30427447
Pereira AS, Willhelm AR, Koller SH, Almeida RMMd. Risk and protective factors for suicide attempt in emerging adulthood. Ciencia & saude coletiva. 2018;23:3767–77.30427447
27. Ghose B Wang R Tang S Yaya S Engagement in physical activity, suicidal thoughts and suicide attempts among older people in five developing countries PeerJ 2019 7 e7108 10.7717/peerj.7108 31223536
Ghose B, Wang R, Tang S, Yaya S. Engagement in physical activity, suicidal thoughts and suicide attempts among older people in five developing countries. PeerJ. 2019;7: e7108. 31223536
28. Cho K-O Physical activity and suicide attempt of south Korean adolescents-evidence from the eight Korea youth risk behaviors web-based survey J Sports Sci Med 2014 13 4 888 25435782
Cho K-O. Physical activity and suicide attempt of south Korean adolescents-evidence from the eight Korea youth risk behaviors web-based survey. J Sports Sci Med. 2014;13(4):888. 25435782
29. Garmezy N, Masten AS, Tellegen A. The study of stress and competence in children: a building block for developmental psychopathology. Child Dev. 1984;55(1):97–111.
30. Hollister-Wagner GH Foshee VA Jackson C Adolescent aggression: Models of resiliency 1 J Appl Soc Psychol 2001 31 3 445 466 10.1111/j.1559-1816.2001.tb02050.x
Hollister-Wagner GH, Foshee VA, Jackson C. Adolescent aggression: Models of resiliency 1. J Appl Soc Psychol. 2001;31(3):445–66.
31. Masten AS Garmezy N Tellegen A Pellegrini DS Larkin K Larsen A Competence and stress in school children: The moderating effects of individual and family qualities J Child Psychol Psychiatry 1988 29 6 745 764 10.1111/j.1469-7610.1988.tb00751.x 3235488
Masten AS, Garmezy N, Tellegen A, Pellegrini DS, Larkin K, Larsen A. Competence and stress in school children: The moderating effects of individual and family qualities. J Child Psychol Psychiatry. 1988;29(6):745–64. 3235488
32. McLaren S Gomez R Bailey M Van Der Horst RK The association of depression and sense of belonging with suicidal ideation among older adults: Applicability of resiliency models Suicide and Life-Threatening Behavior 2007 37 1 89 102 10.1521/suli.2007.37.1.89 17397283
McLaren S, Gomez R, Bailey M, Van Der Horst RK. The association of depression and sense of belonging with suicidal ideation among older adults: Applicability of resiliency models. Suicide and Life-Threatening Behavior. 2007;37(1):89–102. 17397283
33. Asadi-Lari M, Vaez Mahdavi MR, Faghihzadeh S, Montazeri A, Farshad A, Kalantari N, et al. The Application of Urban Health Equity Aassessment and Response Tool (Urban HEART) in Tehran; Concepts and Framework. Med J Islam Repub Iran. 2010;24(3):175–85.
34. Asadi-Lari M Vaez-Mahdavi MR Faghihzadeh S Cherghian B Esteghamati A Farshad AA Response-oriented measuring inequalities in Tehran: second round of UrbanHealth Equity Assessment and Response Tool (Urban HEART-2), concepts and framework Med J Islam Repub Iran 2013 27 4 236 24926187
Asadi-Lari M, Vaez-Mahdavi MR, Faghihzadeh S, Cherghian B, Esteghamati A, Farshad AA, et al. Response-oriented measuring inequalities in Tehran: second round of UrbanHealth Equity Assessment and Response Tool (Urban HEART-2), concepts and framework. Med J Islam Repub Iran. 2013;27(4):236. 24926187
35. Tofighi S Zaboli R Vaez Mahdavi MR Rezapoor A Moradi M Golmakani MM The healthcare costs in the aging based on data from the Urban Health Equity Assessment and Response Tool project in Tehran, Iran (UHEART-2) International Journal of Medical Reviews 2015 2 1 201 207
Tofighi S, Zaboli R, Vaez Mahdavi MR, Rezapoor A, Moradi M, Golmakani MM, et al. The healthcare costs in the aging based on data from the Urban Health Equity Assessment and Response Tool project in Tehran, Iran (UHEART-2). International Journal of Medical Reviews. 2015;2(1):201–7.
36. Sheppard P Monden C When does family size matter? Sibship size, socioeconomic status and education in England Evolutionary Human Sciences 2020 2 e51 10.1017/ehs.2020.54 37588352
Sheppard P, Monden C. When does family size matter? Sibship size, socioeconomic status and education in England. Evolutionary Human Sciences. 2020;2: e51. 37588352
37. Kılıç C General Health Questionnaire: validity and reliability Turk J Psychiatry 1996 7 3 9
Kılıç C. General Health Questionnaire: validity and reliability. Turk J Psychiatry. 1996;7:3–9.
38. Montazeri A Harirchi AM Shariati M Garmaroudi G Ebadi M Fateh A The 12-item General Health Questionnaire (GHQ-12): translation and validation study of the Iranian version Health Qual Life Outcomes 2003 1 1 4 10.1186/1477-7525-1-1 12605709
Montazeri A, Harirchi AM, Shariati M, Garmaroudi G, Ebadi M, Fateh A. The 12-item General Health Questionnaire (GHQ-12): translation and validation study of the Iranian version. Health Qual Life Outcomes. 2003;1:1–4. 12605709
39. Noorbala AA Bagheri Yazdi SA Asadi Lari M Vaez Mahdavi MR Mental health status of individuals fifteen years and older in Tehran-Iran (2009) Iranian journal of psychiatry and clinical psychology 2011 16 4 479 483
Noorbala AA, Bagheri Yazdi SA, Asadi Lari M, Vaez Mahdavi MR. Mental health status of individuals fifteen years and older in Tehran-Iran (2009). Iranian journal of psychiatry and clinical psychology. 2011;16(4):479–83.
40. Koeter MW Validity of the GHQ and SCL anxiety and depression scales: a comparative study J Affect Disord 1992 24 4 271 279 10.1016/0165-0327(92)90112-J 1578083
Koeter MW. Validity of the GHQ and SCL anxiety and depression scales: a comparative study. J Affect Disord. 1992;24(4):271–9. 1578083
41. Goldney RD Winefield AH Tiggemann M Winefield HR Smith S Suicidal ideation in a young adult population Acta Psychiatr Scand 1989 79 5 481 489 10.1111/j.1600-0447.1989.tb10291.x 2750549
Goldney RD, Winefield AH, Tiggemann M, Winefield HR, Smith S. Suicidal ideation in a young adult population. Acta Psychiatr Scand. 1989;79(5):481–9. 2750549
42. Pompili M Rihmer Z Akiskal HS Innamorati M Iliceto P Akiskal KK Temperament and personality dimensions in suicidal and nonsuicidal psychiatric inpatients Psychopathology 2008 41 5 313 321 10.1159/000146069 18635934
Pompili M, Rihmer Z, Akiskal HS, Innamorati M, Iliceto P, Akiskal KK, et al. Temperament and personality dimensions in suicidal and nonsuicidal psychiatric inpatients. Psychopathology. 2008;41(5):313–21. 18635934
43. Rosenberg M Society and the adolescent self-image Princeton 1965 NJ Princeton University Press
Rosenberg M. Society and the adolescent self-image Princeton. NJ: Princeton University Press; 1965.
44. Srole L Social integration and certain corollaries: An exploratory study Am Sociol Rev 1956 21 6 709 716 10.2307/2088422
Srole L. Social integration and certain corollaries: An exploratory study. Am Sociol Rev. 1956;21(6):709–16.
45. Nowicki S Duke MP A Locus of Control Scale for Noncollege as Well as College Adults J Pers Assess 1974 38 2 136 137 10.1080/00223891.1974.10119950
Nowicki S, Duke MP. A Locus of Control Scale for Noncollege as Well as College Adults. J Pers Assess. 1974;38(2):136–7.
46. Goldberg DP Hillier VF A scaled version of the General Health Questionnaire Psychol Med 1979 9 1 139 145 10.1017/S0033291700021644 424481
Goldberg DP, Hillier VF. A scaled version of the General Health Questionnaire. Psychol Med. 1979;9(1):139–45. 424481
47. Noormohammadpour P Mansournia MA Koohpayehzadeh J Asgari F Rostami M Rafei A Prevalence of chronic neck pain, low back pain, and knee pain and their related factors in community-dwelling adults in Iran Clin J Pain 2017 33 2 181 187 10.1097/AJP.0000000000000396 27258995
Noormohammadpour P, Mansournia MA, Koohpayehzadeh J, Asgari F, Rostami M, Rafei A, et al. Prevalence of chronic neck pain, low back pain, and knee pain and their related factors in community-dwelling adults in Iran. Clin J Pain. 2017;33(2):181–7. 27258995
48. Organization WH. Global physical activity questionnaire (GPAQ) analysis guide. Geneva: World Health Organization. 2012:1–22. Available at: http://www.who.int/chp/steps/resources/GPAQ_Analysis_Guide.pdf.
49. Esteghamati A Khalilzadeh O Rashidi A Kamgar M Meysamie A Abbasi M Physical activity in Iran: results of the third national surveillance of risk factors of non-communicable diseases (SuRFNCD-2007) J Phys Act Health 2011 8 1 27 35 10.1123/jpah.8.1.27 21297182
Esteghamati A, Khalilzadeh O, Rashidi A, Kamgar M, Meysamie A, Abbasi M. Physical activity in Iran: results of the third national surveillance of risk factors of non-communicable diseases (SuRFNCD-2007). J Phys Act Health. 2011;8(1):27–35. 21297182
50. Bull FC Maslin TS Armstrong T Global physical activity questionnaire (GPAQ): nine country reliability and validity study J Phys Act Health 2009 6 6 790 804 10.1123/jpah.6.6.790 20101923
Bull FC, Maslin TS, Armstrong T. Global physical activity questionnaire (GPAQ): nine country reliability and validity study. J Phys Act Health. 2009;6(6):790–804. 20101923
51. Bangasser DA Cuarenta A Sex differences in anxiety and depression: circuits and mechanisms Nat Rev Neurosci 2021 22 11 674 684 10.1038/s41583-021-00513-0 34545241
Bangasser DA, Cuarenta A. Sex differences in anxiety and depression: circuits and mechanisms. Nat Rev Neurosci. 2021;22(11):674–84. 34545241
52. Wohlgemuth KJ Arieta LR Brewer GJ Hoselton AL Gould LM Smith-Ryan AE Sex differences and considerations for female specific nutritional strategies: a narrative review J Int Soc Sports Nutr 2021 18 1 27 10.1186/s12970-021-00422-8 33794937
Wohlgemuth KJ, Arieta LR, Brewer GJ, Hoselton AL, Gould LM, Smith-Ryan AE. Sex differences and considerations for female specific nutritional strategies: a narrative review. J Int Soc Sports Nutr. 2021;18(1):27. 33794937
53. Biswas T, Scott JG, Munir K, Renzaho AMN, Rawal LB, Baxter J, et al. Global variation in the prevalence of suicidal ideation, anxiety and their correlates among adolescents: A population based study of 82 countries. EClinicalMedicine. 2020;24:100395.
54. Coleman D, Kaplan MS, Casey JT. The social nature of male suicide: A new analytic model. International Journal of Men's Health. 2011;10(3):240–52.
55. Kleiman EM Liu RT Social support as a protective factor in suicide: Findings from two nationally representative samples J Affect Disord 2013 150 2 540 545 10.1016/j.jad.2013.01.033 23466401
Kleiman EM, Liu RT. Social support as a protective factor in suicide: Findings from two nationally representative samples. J Affect Disord. 2013;150(2):540–5. 23466401
56. Nowotny KM Peterson RL Boardman JD Gendered contexts: variation in suicidal ideation by female and male youth across US states J Health Soc Behav 2015 56 1 114 130 10.1177/0022146514568350 25722128
Nowotny KM, Peterson RL, Boardman JD. Gendered contexts: variation in suicidal ideation by female and male youth across US states. J Health Soc Behav. 2015;56(1):114–30. 25722128
57. Xu H Zhang W Wang X Yuan J Tang X Yin Y Prevalence and influence factors of suicidal ideation among females and males in Northwestern urban China: a population-based epidemiological study BMC Public Health 2015 15 1 13 10.1186/s12889-015-2257-5 25563658
Xu H, Zhang W, Wang X, Yuan J, Tang X, Yin Y, et al. Prevalence and influence factors of suicidal ideation among females and males in Northwestern urban China: a population-based epidemiological study. BMC Public Health. 2015;15:1–13. 25563658
58. Tian L Yang Y Yang H Huebner ES Prevalence of suicidal ideation and its association with positive affect in working women: A day reconstruction study Front Psychol 2017 8 231578 10.3389/fpsyg.2017.00285
Tian L, Yang Y, Yang H, Huebner ES. Prevalence of suicidal ideation and its association with positive affect in working women: A day reconstruction study. Front Psychol. 2017;8: 231578.
59. Kerr DC Owen LD Pears KC Capaldi DM Prevalence of suicidal ideation among boys and men assessed annually from ages 9 to 29 years Suicide and Life-Threatening Behavior 2008 38 4 390 402 10.1521/suli.2008.38.4.390 18724787
Kerr DC, Owen LD, Pears KC, Capaldi DM. Prevalence of suicidal ideation among boys and men assessed annually from ages 9 to 29 years. Suicide and Life-Threatening Behavior. 2008;38(4):390–402. 18724787
60. Nock MK Borges G Bromet EJ Cha CB Kessler RC Lee S Suicide and suicidal behavior Epidemiologic reviews 2008 30 1 133 10.1093/epirev/mxn002 18653727
Nock MK, Borges G, Bromet EJ, Cha CB, Kessler RC, Lee S. Suicide and suicidal behavior Epidemiologic reviews. 2008;30(1):133. 18653727
61. Kourtis AP Kraft JM Gavin L Kissin D McMichen-Wright P Jamieson DJ Prevention of sexually transmitted human immunodeficiency virus (HIV) infection in adolescents Curr HIV Res 2006 4 2 209 219 10.2174/157016206776055057 16611059
Kourtis AP, Kraft JM, Gavin L, Kissin D, McMichen-Wright P, Jamieson DJ. Prevention of sexually transmitted human immunodeficiency virus (HIV) infection in adolescents. Curr HIV Res. 2006;4(2):209–19. 16611059
62. Lewinsohn PM Rohde P Seeley JR Psychosocial risk factors for future adolescent suicide attempts J Consult Clin Psychol 1994 62 2 297 10.1037/0022-006X.62.2.297 8201067
Lewinsohn PM, Rohde P, Seeley JR. Psychosocial risk factors for future adolescent suicide attempts. J Consult Clin Psychol. 1994;62(2):297. 8201067
63. Dishion TJ Loeber R Adolescent marijuana and alcohol use: The role of parents and peers revisited Am J Drug Alcohol Abuse 1985 11 1–2 11 25 10.3109/00952998509016846 4061428
Dishion TJ, Loeber R. Adolescent marijuana and alcohol use: The role of parents and peers revisited. Am J Drug Alcohol Abuse. 1985;11(1–2):11–25. 4061428
64. Barber BK. Introduction:Adolescent Socialization in Context-the Role of Connection, Regulation, and Autonomy in the Family. J Adolesc Res. 1997;12(1):5–11.
65. Patterson GR, Stouthamer-Loeber M. The correlation of family management practices and delinquency. Child development. 1984:1299–307.
66. Ernst M Klein EM Beutel ME Brähler E Gender-specific associations of loneliness and suicidal ideation in a representative population sample: young, lonely men are particularly at risk J Affect Disord 2021 294 63 70 10.1016/j.jad.2021.06.085 34274789
Ernst M, Klein EM, Beutel ME, Brähler E. Gender-specific associations of loneliness and suicidal ideation in a representative population sample: young, lonely men are particularly at risk. J Affect Disord. 2021;294:63–70. 34274789
67. Xiao Y Lindsey MA Racial/ethnic, sex, sexual orientation, and socioeconomic disparities in suicidal trajectories and mental health treatment among adolescents transitioning to young adulthood in the USA: A population-based cohort study Administration and Policy in Mental Health and Mental Health Services Research 2021 48 742 756 10.1007/s10488-021-01122-w 33629220
Xiao Y, Lindsey MA. Racial/ethnic, sex, sexual orientation, and socioeconomic disparities in suicidal trajectories and mental health treatment among adolescents transitioning to young adulthood in the USA: A population-based cohort study. Administration and Policy in Mental Health and Mental Health Services Research. 2021;48:742–56. 33629220
68. Xiao Y Lindsey MA Adolescent social networks matter for suicidal trajectories: disparities across race/ethnicity, sex, sexual identity, and socioeconomic status Psychol Med 2022 52 15 3677 3688 10.1017/S0033291721000465
Xiao Y, Lindsey MA. Adolescent social networks matter for suicidal trajectories: disparities across race/ethnicity, sex, sexual identity, and socioeconomic status. Psychol Med. 2022;52(15):3677–88.
69. Kim SM Han DH Trksak GH Lee YS Gender differences in adolescent coping behaviors and suicidal ideation: findings from a sample of 73,238 adolescents Anxiety Stress Coping 2014 27 4 439 454 10.1080/10615806.2013.876010 24344782
Kim SM, Han DH, Trksak GH, Lee YS. Gender differences in adolescent coping behaviors and suicidal ideation: findings from a sample of 73,238 adolescents. Anxiety Stress Coping. 2014;27(4):439–54. 24344782
70. Ibrahim N, Amit N, Che Din N, Ong HC. Gender differences and psychological factors associated with suicidal ideation among youth in Malaysia. Psychol Res Behav Manag. 2017;10:129–35.
71. https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Gesundheit/Todesursachen/Tabellen/suizide.html.
72. Bogdanovica I Jiang G-X Löhr C Schmidtke A Mittendorfer-Rutz E Changes in rates, methods and characteristics of suicide attempters over a 15-year period: comparison between Stockholm, Sweden, and Würzburg Germany Social psychiatry and psychiatric epidemiology 2011 46 1103 1114 10.1007/s00127-010-0282-3 20820754
Bogdanovica I, Jiang G-X, Löhr C, Schmidtke A, Mittendorfer-Rutz E. Changes in rates, methods and characteristics of suicide attempters over a 15-year period: comparison between Stockholm, Sweden, and Würzburg. Germany Social psychiatry and psychiatric epidemiology. 2011;46:1103–14. 20820754
73. Achté K Suicidal tendencies in the elderly Suicide and Life-Threatening Behavior 1988 18 1 55 10.1111/j.1943-278X.1988.tb00141.x 3388470
Achté K. Suicidal tendencies in the elderly. Suicide and Life-Threatening Behavior. 1988;18(1):55. 3388470
74. Cano-Montalbán I Quevedo-Blasco R Las variables sociodemográficas más asociadas con el comportamiento suicida y con los métodos suicidas en Europa y América. Una revisión sistemática. Eur J Psychol Applied Legal Context 2018 10 1 15 25 10.5093/ejpalc2018a2
Cano-Montalbán I, Quevedo-Blasco R. Las variables sociodemográficas más asociadas con el comportamiento suicida y con los métodos suicidas en Europa y América. Una revisión sistemática. Eur J Psychol Applied Legal Context. 2018;10(1):15–25.
75. Duberstein PR Conwell Y Conner KR Eberly S Caine ED Suicide at 50 years of age and older: perceived physical illness, family discord and financial strain Psychol Med 2004 34 1 137 146 10.1017/S0033291703008584 14971634
Duberstein PR, Conwell Y, Conner KR, Eberly S, Caine ED. Suicide at 50 years of age and older: perceived physical illness, family discord and financial strain. Psychol Med. 2004;34(1):137–46. 14971634
76. Janiri D Doucet GE Pompili M Sani G Luna B Brent DA Risk and protective factors for childhood suicidality: a US population-based study The Lancet Psychiatry 2020 7 4 317 326 10.1016/S2215-0366(20)30049-3 32171431
Janiri D, Doucet GE, Pompili M, Sani G, Luna B, Brent DA, et al. Risk and protective factors for childhood suicidality: a US population-based study. The Lancet Psychiatry. 2020;7(4):317–26. 32171431
77. Osman A Barrios FX Gutierrez PM Wrangham JJ Kopper BA Truelove RS The Positive and Negative Suicide Ideation (PANSI) Inventory: Psychometric evaluation with adolescent psychiatric inpatient samples J Pers Assess 2002 79 3 512 530 10.1207/S15327752JPA7903_07 12511018
Osman A, Barrios FX, Gutierrez PM, Wrangham JJ, Kopper BA, Truelove RS, et al. The Positive and Negative Suicide Ideation (PANSI) Inventory: Psychometric evaluation with adolescent psychiatric inpatient samples. J Pers Assess. 2002;79(3):512–30. 12511018
78. Johnson J Wood AM Gooding P Taylor PJ Tarrier N Resilience to suicidality: The buffering hypothesis Clin Psychol Rev 2011 31 4 563 591 10.1016/j.cpr.2010.12.007 21276646
Johnson J, Wood AM, Gooding P, Taylor PJ, Tarrier N. Resilience to suicidality: The buffering hypothesis. Clin Psychol Rev. 2011;31(4):563–91. 21276646
79. Li J-B Yang A Dou K Cheung RY Self-control moderates the association between perceived severity of coronavirus disease 2019 (COVID-19) and mental health problems among the Chinese public Int J Environ Res Public Health 2020 17 13 4820 10.3390/ijerph17134820 32635495
Li J-B, Yang A, Dou K, Cheung RY. Self-control moderates the association between perceived severity of coronavirus disease 2019 (COVID-19) and mental health problems among the Chinese public. Int J Environ Res Public Health. 2020;17(13):4820. 32635495
80. Lee CG Cho Y Yoo S The relations of suicidal ideation and attempts with physical activity among Korean adolescents J Phys Act Health 2013 10 5 716 726 10.1123/jpah.10.5.716 23036894
Lee CG, Cho Y, Yoo S. The relations of suicidal ideation and attempts with physical activity among Korean adolescents. J Phys Act Health. 2013;10(5):716–26. 23036894
81. Parker G Hawkins J Weigel C Fanning L Round T Reyna K Adolescent suicide prevention: the Oklahoma community reaches out The Journal of Continuing Education in Nursing 2009 40 4 177 180 10.3928/00220124-20090401-08 19418757
Parker G, Hawkins J, Weigel C, Fanning L, Round T, Reyna K. Adolescent suicide prevention: the Oklahoma community reaches out. The Journal of Continuing Education in Nursing. 2009;40(4):177–80. 19418757
82. Stanley B Brown GK Karlin B Kemp J VonBergen H Safety plan treatment manual to reduce suicide risk: Veteran version 2008 Washington, DC United States Department of Veterans Affairs 12
Stanley B, Brown GK, Karlin B, Kemp J, VonBergen H. Safety plan treatment manual to reduce suicide risk: Veteran version. Washington, DC: United States Department of Veterans Affairs; 2008. p. 12.
83. Cairney J Kwan MY Veldhuizen S Faulkner GE Who uses exercise as a coping strategy for stress? Results from a national survey of Canadians J Phys Act Health 2014 11 5 908 916 10.1123/jpah.2012-0107 23493043
Cairney J, Kwan MY, Veldhuizen S, Faulkner GE. Who uses exercise as a coping strategy for stress? Results from a national survey of Canadians. J Phys Act Health. 2014;11(5):908–16. 23493043
84. Tucker RP Crowley KJ Davidson CL Gutierrez PM Risk Factors, Warning Signs, and Drivers of Suicide: What Are They, How Do They Differ, and Why Does It Matter? Suicide Life Threat Behav 2015 45 6 679 689 10.1111/sltb.12161 25858332
Tucker RP, Crowley KJ, Davidson CL, Gutierrez PM. Risk Factors, Warning Signs, and Drivers of Suicide: What Are They, How Do They Differ, and Why Does It Matter? Suicide Life Threat Behav. 2015;45(6):679–89. 25858332
85. Bentley KH Franklin JC Ribeiro JD Kleiman EM Fox KR Nock MK Anxiety and its disorders as risk factors for suicidal thoughts and behaviors: A meta-analytic review Clin Psychol Rev 2016 43 30 46 10.1016/j.cpr.2015.11.008 26688478
Bentley KH, Franklin JC, Ribeiro JD, Kleiman EM, Fox KR, Nock MK. Anxiety and its disorders as risk factors for suicidal thoughts and behaviors: A meta-analytic review. Clin Psychol Rev. 2016;43:30–46. 26688478
86. Wenzel A, Brown GK, Beck AT. Cognitive therapy for suicidal patients: Scientific and clinical applications. Washington, DC: American Psychological Association; 2009.
87. Wenzel A Beck AT A cognitive model of suicidal behavior: Theory and treatment Appl Prev Psychol 2008 12 4 189 201 10.1016/j.appsy.2008.05.001
Wenzel A, Beck AT. A cognitive model of suicidal behavior: Theory and treatment. Appl Prev Psychol. 2008;12(4):189–201.
88. Hornig CD McNally RJ A Reanalysis of Data from the Epidemiologic Catchment Area Study Br J Psychiatry 1995 167 1 76 79 10.1192/bjp.167.1.76 7551614
Hornig CD, McNally RJ. A Reanalysis of Data from the Epidemiologic Catchment Area Study. Br J Psychiatry. 1995;167(1):76–9. 7551614
89. Warshaw MG Massion AO Peterson LG Pratt LA Keller MB Suicidal behavior in patients with panic disorder: retrospective and prospective data J Affect Disord 1995 34 3 235 247 10.1016/0165-0327(95)00022-F 7560552
Warshaw MG, Massion AO, Peterson LG, Pratt LA, Keller MB. Suicidal behavior in patients with panic disorder: retrospective and prospective data. J Affect Disord. 1995;34(3):235–47. 7560552
90. Mars B Heron J Klonsky ED Moran P O'Connor RC Tilling K What distinguishes adolescents with suicidal thoughts from those who have attempted suicide? A population-based birth cohort study J Child Psychol Psychiatry 2019 60 1 91 99 10.1111/jcpp.12878 29492978
Mars B, Heron J, Klonsky ED, Moran P, O’Connor RC, Tilling K, et al. What distinguishes adolescents with suicidal thoughts from those who have attempted suicide? A population-based birth cohort study. J Child Psychol Psychiatry. 2019;60(1):91–9. 29492978
91. Bentley KH Franklin JC Ribeiro JD Kleiman EM Fox KR Nock MK Anxiety and its disorders as risk factors for suicidal thoughts and behaviors: A meta-analytic review Clin Psychol Rev 2016 43 30 46 10.1016/j.cpr.2015.11.008 26688478
Bentley KH, Franklin JC, Ribeiro JD, Kleiman EM, Fox KR, Nock MK. Anxiety and its disorders as risk factors for suicidal thoughts and behaviors: A meta-analytic review. Clin Psychol Rev. 2016;43:30–46. 26688478
