Sage Journals: Discover world-class research

Abstract

Objectives

Adolescents with a chronic medical condition (CMC) are at greater risk of mental health difficulties, but demographic factors and subjective health may confound this relationship.

Design

Using data from a nationally representative adolescent sample from Northern Ireland (N = 1,299), we examined whether three CMC categories were associated with symptoms of depression, anxiety, posttraumatic stress disorder, and with suicidal thoughts or plans, and attempts.

Methods

Hierarchical multiple regression analyses were conducted to test whether the CMC classifications explained a significant proportion of the variance across the mental health variables, while controlling for age, sex, and subjective health. A multinomial logistic regression analysis was conducted to test whether the CMC classifications were associated with suicidality.

Results

CMC categories explained a small but statistically significant proportion of variance in mental health. Age was associated with suicidal thoughts or plans, and suicide attempts. Subjective health emerged as the factor most strongly linked to all criterion variables except suicidality.

Conclusions

Subjective health may be more strongly related to adolescent mental health than previously identified. Future research could explore potential psychosocial factors associated with these CMC classifications to clarify the links between CMCs and mental health.

Plain Language Summary

The relationship between having a chronic medical condition, mental health problems, and thinking about, planning, or attempting suicide: Teenagers with long-term physical health conditions are more likely to experience mental health difficulties, but this link may be explained by age, sex, and how healthy young people feel overall. This study used data from a large representative sample of teenagers in Northern Ireland to explore whether different types of chronic conditions were linked to depression, anxiety, post-traumatic stress disorder, and suicidal thoughts, plans, or attempts. Chronic medical conditions were linked to slightly higher levels of mental health symptoms overall. Older teenagers were more likely to report suicidal thoughts, plans, or attempts. How healthy teenagers felt was the factor most strongly related to mental health, except for suicidal thoughts, plans, or attempts. Teenagers’ own perspectives of their health may be more important for mental health than previously recognised. Future research could explore the social and psychological factors linked with chronic conditions to better understand how physical health and mental health are connected.

Keywords

depression anxiety youth chronic illness posttraumatic stress suicide

The peak age of onset for most mental health disorders occurs during late adolescence (Luo et al., 2024; Pfeifer & Allen, 2020). Depression and anxiety are common issues among adolescents with approximately 10.0% diagnosed with major depressive disorder, and 6.5% diagnosed with an anxiety disorder (Liu et al., 2024) - at least twice as many experience ‘sub-syndromal’ levels of depression and anxiety – and these mental health problems are associated with an increased risk of suicidality (Horn et al., 2021; Noyes et al., 2022). Over 700,000 people die by suicide every year, ranking as the third leading cause of death among adolescents (World Health Organization [WHO], 2025b). Northern Ireland has the highest rate of suicide among young people aged 15–24 in the United Kingdom at 17.8 per 100,000 people (Royal College of Pediatrics and Child Health, 2020).

One group who may be particularly at risk of these mental health and suicide sequelae are adolescents with a chronic medical condition (CMC). Globally, 20–30% of adolescents have CMC, with asthma being the most common (Asher & Pearce, 2014; Russo, 2022). CMCs in adolescence often co-occur with depression and anxiety (Brady et al., 2017; Cobham et al., 2018; Dudeney et al., 2024). Being diagnosed with a CMC, receiving invasive treatments, and managing chronic pain can be experienced as traumatizing for adolescents (Meentken et al., 2017; Pinquart, 2018), and higher rates of post-traumatic stress disorder (PTSD) have also been reported in adolescents with a CMC (Eskander et al., 2020; Pinquart, 2018).

There is also evidence that having a CMC is associated with a higher risk of suicidality in adolescence – defined by the American Psychological Association (APA) as the risk of suicide indicated by suicidal ideation, intent, or plans (APA, 2018; Heynemann et al., 2021; Underner et al., 2022; Zhang et al., 2019). Adolescents with a CMC can endure persistent pain, social stigma, social isolation, and impaired daily functioning, all of which can increase the likelihood of suicidality (Iannucci & Nierenberg, 2021). Ideation-to-action frameworks, such as the Interpersonal Theory of Suicide (Van Orden et al., 2010), Integrated Motivational-Volitional theory (O’Connor, 2011), and 3 Step Theory (Klonsky & May, 2015), posit that extreme physical or psychological pain, perceiving oneself as a burden, and thwarted belongingness or connectedness, are key facilitators for suicide ideation and attempts. These risk factors can be experienced as a direct consequence of having a CMC (Miao et al., 2024).

The strength of association between CMCs, mental health problems, and suicidality varies considerably across the literature (Ferro et al., 2017). Such variation may be accounted for by differences in measurement. While many studies account for the physical impacts of CMCs, they differ in how health is measured – some rely on objective indicators like patient health records, while others rely on subjective self-reports. Though not a direct measure, subjective health correlates with objective health status (Wuorela et al., 2020), and many studies support the reliability and validity of subjective health (Postigo-Zegarra et al., 2024). Obtaining subjective health reports of adolescents is increasingly prioritized in clinical practice, as they offer a broad understanding of how adolescents are affected across life domains including mobility, sleep quality, and independence (Dalgleish et al., 2020). Adolescents with good physical functioning are up to fifteen times more likely to report better subjective health scores than those with poor subjective health, and almost 80% less likely to report depressive symptoms (Shi et al., 2022). Regarding the onset of mental health difficulties, older adolescents who identify as female are typically much more prone to internalizing and have a higher risk of suicidal ideation and attempts (Levkovich et al., 2025; Miranda-Mendizabal et al., 2019).

The present study used data from the Northern Ireland Youth Wellbeing Prevalence Survey (Bunting et al., 2022) to examine whether adolescents with a CMC had higher levels of depression, anxiety, and PTSD, and whether they were more likely to have had suicidal thoughts or plans, and to have attempted suicide, whilst controlling for age, gender, and subjective health. Based on the existing evidence, we hypothesized that adolescents with a CMC, irrespective of gender, age, and subjective health status, would report higher levels of depression, anxiety, and PTSD (Brady et al., 2017; Pinquart, 2018), and would be more likely to have had suicidal ideation or plans, and to have attempted suicide (Ferro et al., 2017).

Methods

Participants and Procedures

This study used data collected from the Youth Wellbeing in Northern Ireland Prevalence Study (Bunting et al., 2022). The data comprised a nationally representative sample (N = 3,074) of children, adolescents, and young adults aged 2–19 years. Ethical approval for the original data collection was obtained from the relevant institutional ethics committee, and informed consent was obtained from both parents and participants. Between June 2019 and March 2020, a large representative sample of households in Northern Ireland was randomly drawn using the Pointer database. A total of 21,730 addresses were randomly selected for inclusion. Data collection was funded by the Department of Health Northern Ireland and commissioned by the Health and Social Care Borad in Northern Ireland.

Inclusion Criteria for the Analytic Sample

Those aged 11–19 years (n = 1,299) completed several self-report measures of mental well-being and subjective health and were also asked to disclose any medical conditions they currently had. The mental health measures of interest were depression, anxiety, and PTSD. The current study only focused on those who completed the self-report measures (n = 1,299) of mental health. Table 1 provides demographic information about these participants.

Table 1.

Demographic Information for the Sample (n = 1,299)

	N	%
Sex
Male	662	51.0%
Female	637	49.0%
Living area
Urban	811	62.4%
Rural	367	28.3%
Mixed	121	9.3%
Child ethnic group
White	1240	95.5%
Non-white	58	4.4%
Not reported	1	0.0008%
Child health status
Has a CMC	363	27.9%
Does not have a CMC	891	68.6%
Missing data	45	3.5%
Suicide status
Never thought about or attempted	991	76.3%
Just a brief passing thought	48	3.7%
Had a plan, but did not want to die	34	2.6%
Had a plan and wanted to die	22	1.7%
Attempted but did not want to die	18	1.4%
Attempted and wanted to die	17	1.3%
Prefer not to say	4	0.3%
Missing	165	12.7%

Measures

Diagnosis of a CMC

Participants were asked to report, with the following prompt, whether they had a medical condition: “Here is a list of health problems or conditions which some children or young people may have. Please can you tick below whether you have….” The original survey from the Youth Wellbeing in Northern Ireland Study listed a broad range of acute ailments, injuries, and general symptoms, which we did not focus on. While it is unclear how the original authors arrived at their list of health conditions, we focused only on those recognized by the WHO as chronic or persistent (WHO, 2025a). The list of health conditions used in the current study included asthma, birth defects, blood disorders, cancer, cerebral palsy, chronic fatigue, cystic fibrosis, diabetes, epilepsy, heart conditions, kidney and urinary tract conditions, migraine, missing limbs, stiffness or deformities of the body, muscle diseases, obesity, spina bifida, and stomach and digestion conditions. Owing to the low base frequencies of many of the conditions present in the sample (see Table 2), disease-by-disease analyses were not possible. Instead, these illnesses were grouped using the ICD-11 look-up tool to facilitate the analyses of category-specific effects (WHO, 2022). This clustered the 18 conditions listed above to a more manageable 11 classifications: Respiratory Diseases (n = 180); Circulatory System Diseases (n = 20); Diseases of the Nervous System (n = 83); Disease of the Musculoskeletal System (n = 9); External Causes of Morbidity and Mortality (n = 1); Neoplasms (n = 3); Digestive System Diseases (n = 79); Diseases of the Blood or Blood-Forming Organs (n = 4); Genitourinary Diseases (n = 29); Endocrine, Nutritional, or Metabolic Diseases (n = 23); and Developmental Anomalies (n = 25).

Table 2.

Frequency of Chronic Conditions Present in the Sample (n = 1,299)

Condition	N	%
Respiratory, circulatory, and blood diseases	205	15.8%
Asthma	180	13.9%
Heart condition	20	1.5%
Blood disorder	4	0.3%
Cystic fibrosis	1	0.1%
Digestive, genitourinary, endocrine, nutritional and metabolic diseases	131	10.1%
Stomach condition	79	6.1%
Kidney/UT disease	29	2.3%
Obesity	19	1.5%
Diabetes	4	0.3%
Nervous system, musculoskeletal, and developmental	109	8.4%
Migraine	74	5.7%
Stiffness/deformity	20	1.5%
Muscle condition	9	0.7%
Epilepsy	6	0.5%
Birth condition	4	0.3%
Chronic fatigue	3	0.2%
Cerebral palsy	2	0.2%
Spina bifida	1	0.1%

Note. Some participants reported having a CMC from multiple categories. There were participants categorized under both “respiratory, circulatory, and blood diseases” and “Digestive, genitourinary, endocrine, nutritional and metabolic diseases” (n = 28), “respiratory, circulatory, and blood diseases” and “Nervous system, musculoskeletal, and developmental diseases” (n = 25), and “Digestive, genitourinary, endocrine, nutritional and metabolic diseases” and “Nervous system, musculoskeletal, and developmental diseases” (n = 27). Some participants reported having CMCs from all 3 categories (n = 8).

Due to an under-representation of many diseases, we combined several diagnostic classifications to allow for more stable estimation of associations between CMCs and mental health variables, maintain distinctions between disease classes, and potentially identify disease classifications that are more burdensome for adolescents. These classifications were combined based on broad physiological system overlap and general patterns of disease burdens:

1. Respiratory, Circulatory, and Blood Diseases (n = 197) were grouped based on their co-occurrence and shared links to systemic infection;

2. Digestive, Genitourinary, Endocrine, Nutritional, and Metabolic Diseases (n = 126) were grouped based on their roles in metabolic functioning; and

3. Nervous System Diseases, Musculoskeletal Diseases, and Developmental Anomalies (n = 109) were combined due to their early-life onset, chronic progression, and impact on developmental functioning (note: Neoplasms and External Causes of Mortality were excluded from analyses as these were under-represented and could not meaningfully be combined with other classifications).

Depression and Anxiety Symptoms

Participants completed the full 47-item version of the Revised Children’s Anxiety and Depression Scale (RCADS) (Chorpita et al., 2000). While the RCADS assesses subdomains of anxiety such as generalized anxiety, social phobia, separation anxiety, obsessive-compulsive disorder, and panic disorder, total anxiety scores are obtainable by summing scores across the anxiety subscales. In the present dataset, participants reported how often they experienced each symptom using a 4-point Likert scale (“Never” = 0, “Sometimes” = 1, “Often” = 2, “Always” = 3). The RCADS does not provide participants with a timeframe on which to base their responses. The depression subscale comprises 10 items, and the anxiety subscale comprises 37 items. Depression scores range from 0 to 30, and anxiety scores range from 0 to 104, and in both cases, higher scores indicate higher symptom scores. The internal reliability scores for the depression (Cronbach’s α = 0.90) and anxiety (Cronbach’s α = 0.96) scales in this sample were high.

PTSD Symptoms

Participants completed the International Trauma Questionnaire – Child and Adolescent version (ITQ-CA) (Cloitre et al., 2018), which is a self-report measure of ICD-11 PTSD and Complex PTSD symptoms. The PTSD subscale is comprised of six indicators and participants report how often they experienced each symptom over the last month on a scale of 0–4 (0 = “never,” 1 = “a little bit,” 2 = “sometimes,” 3 = “a lot,” 4 = “almost always”). PTSD scores range from 0–24, with higher scores indicating higher levels of PTSD. Previous studies have found support for the psychometric properties of the ITQ-CA (Ho et al., 2022). The internal reliability of the PTSD scale scores in this sample was satisfactory (Cronbach’s α = 0.88).

Indicators of Suicidality

Participants were asked, “Have you ever thought about or attempted to kill yourself?,” which is an item taken from the Suicide Behaviors Questionnaire (SBQ-R) (Osman et al., 2001). Response options were: 1 = “never,” 2 = “it was just a brief passing thought,” 3 = “I have had a plan at least once to kill myself but did not try to do it,” 4 = “I have had a plan at least once to kill myself and really wanted to do it,” 5 = “I have had attempted to kill myself, but did not want to die,” and 6 = “I have attempted to kill myself, and really hoped to die.” Owing to low frequencies across the categories (i.e., response option 5, n = 18; response option 6, n = 17), and recognizing important differences between suicidal ideation and suicidal behavior (Klonsky et al., 2021), responses were recoded into three categories representing ‘no suicidal thoughts or attempts’ (i.e., original response option of 1, n = 991), ‘suicidal thoughts or plans’ (i.e., original response options 2, 3, 4, n = 104), and ‘suicide attempt’ (i.e., original response options 5 and 6, n = 35). Frequencies for each recoded response are presented in Table 1.

Subjective Health Status

Participants reported their general health on a 5-point Likert scale using the following prompt: “How is your health in general?” The scale was coded 1 (very bad) to 5 (very good). Participants were not provided with a timeframe. While full scales designed to assess subjective health exist and have proven reliable (Bart et al., 2018), the single item above is widely used across large epidemiological studies like the Canadian Health Survey on Children and Youth, which utilized a scale from 1 (poor) to 5 (excellent) (Wang et al., 2023). Subjective health measures like this have consistently been shown to be as reliable and valid as objective measures of health (Hamplová et al., 2022).

Data Analysis

Descriptive statistics were used to summarize scores on the measures of depression, anxiety, and PTSD. Data distributions were inspected for normality to ensure the data were suitable for analyses. Given that assumptions of linearity between independent variables and the dependent variables, multicollinearity across independent variables, and homoscedasticity were met, three hierarchical multiple regression analyses were employed to determine unique associations with each mental health variable (i.e., depression, anxiety, and PTSD). In step 1 of each model, age, sex, and subjective health were entered, while at step two, the three CMC classifications (i.e., Respiratory, Circulatory, and Blood Diseases; Digestive, Genitourinary, Endocrine, Nutritional, and Metabolic Diseases; and Nervous System Diseases, Musculoskeletal Diseases, and Developmental Anomalies) were entered as dummy variables. This ordering tests if each CMC class is uniquely associated with mental health problems, above and beyond the influence of known risk factors for mental health problems. The suicide variable was recoded to include three categories (0 = no suicidal thoughts or behavior, 1 = suicidal thoughts or plans, and 2 = suicidal attempt) so a multinomial logistic regression was conducted to test how age, sex, subjective health, and CMCs classes were related to suicidal thoughts or plans, and suicidal attempt. All analyses were conducted in IBM SPSS version 30.

Results

Descriptive Statistics

The mean age of the sample participants was 15.16 years (Mdn = 15.00, SD = 2.58, range = 11–19). Information on CMCs is presented in Table 2. Overall, 27.9% (n = 363) of participants reported having a CMC, and the most commonly reported CMC was asthma (13.9%). Among all participants, 8.0% reported having thought about suicide or having made a plan, and 2.7% had attempted suicide. Scores for depression, anxiety, and PTSD were all positively skewed, indicating relatively low levels on average for these variables. Scores for subjective health were highly negatively skewed, indicating high levels of subjective health, on average (see Table 3).

Table 3.

Descriptive Statistics for Continuous Variables

	Mean (SD)	Std. Error mean	Median	Range
Depression	6.10 (5.58)	0.16	5.00	0–30
Anxiety	25.66 (19.47)	0.57	20.00	0–104
PTSD	4.90 (5.36)	0.24	3.00	0–24
Subjective health	4.35 (.76)	0.02	4.50	1–5

Note. PTSD = post-traumatic stress disorder, SD = standard deviation.

Hierarchical Multiple Regression Models of Depression, Anxiety, and PTSD

Each hierarchical multiple regression model was statistically significant: depression, F (6, 1168) = 44.52, p < .001; anxiety, F (6, 1166) = 31.67, p < .001; and PTSD, F (6, 500) = 10.96, p < .001. Results of these analyses are presented in Table 4.

Table 4.

Hierarchical Multiple Regression Models of Depression, Anxiety, and PTSD

	Depression	Anxiety	PTSD
Step 1
Age	0.05	0.01	0.05
Sex	0.12***	0.24***	0.14***
Subjective health	−0.38***	−0.25***	−0.26***
R²	0.17***	0.12***	0.10***
Step 2
ΔR²	0.02***	0.02***	0.01***
Age	0.04	0.01	0.05
Sex	0.10***	0.22***	0.13**
Subjective health	−0.34***	−0.20***	−0.22***
Respiratory, circulatory, blood	0.01	0.02	0.09*
Digestive, genitourinary, endocrine, nutritional, metabolic	0.04	0.08**	0.05
Nervous system, musculoskeletal, developmental	0.12***	0.11***	0.05
R²	0.19***	0.14***	0.11***

Note. Values represent standardized beta values; R² = variance explained by the model; ΔR² = additional variance explained from step 1 to step 2; * = p < .05; ** = p < .01; *** = p < .001.

In Step 1, age, sex and subjective health status explained 17%, 12%, and 10% of the variance in depression, anxiety, and PTSD scores, respectively. In Step 2, the addition of the CMC classifications explained a small but statistically significant proportion of variance in depression (R² change = 0.02, p < .001), anxiety (R² change = 0.02, p < .001), and PTSD (R² change = 0.01, p < .001) scores.

Nervous System, Musculoskeletal, and Developmental Diseases were significantly associated with higher levels of depression (β = 0.12, p < .001) and anxiety (β = 0.11, p < .001); Digestive, Genitourinary, Endocrine, and Metabolic Diseases were associated with higher levels of anxiety (β = 0.08, p = .004); and Respiratory, Circulatory and Blood Diseases were associated with higher levels of PTSD (β = 0.09, p = .041). Of the covariates in the model, being female was associated with higher levels of depression (β = 0.10, p < .001), anxiety (β = .22, p < .001), and PTSD (β = 0.13, p = .003). Better subjective health status was associated with lower levels of depression (β = −0.34, p < .001), anxiety (β = −0.20, p < .001), and PTSD (β = −0.22, p < .001).

Multinomial Logistic Regression Model of Suicide Status

The multinomial logistic regression model was statistically significant (χ² (12, 1,082) = 71.84, p < .001) and explained between 6.4% (Cox and Snell) and 11.0% (Nagelkerke) of the variance in suicide status. As can be seen in Table 5, only older age of the participant was significantly associated with having suicidal thoughts or a plan (OR = 1.35, p < .001), and having attempted suicide (OR = 1.49, p < .001).

Table 5.

Multinomial Logistic Regression Model of Suicide Categories

Variable	B	SE	Wald	p	OR (95%CI)
Suicide ideation/plan
Age	0.30	0.05	34.43	<.001	1.35 (1.22/1.50)
Sex	0.29	0.22	1.64	.20	1.33 (0.86/2.06)
Subjective health	0.05	0.15	0.12	.73	1.06 (0.78/1.42)
Respiratory, circulatory, blood diseases	−0.20	0.33	0.36	.55	0.82 (0.43/1.57)
Digestive, genitourinary, endocrine, nutritional, metabolic	0.004	0.35	<.001	.99	1.00 (0.51/2.00)
Nervous system, musculoskeletal, developmental	0.17	0.37	0.22	.64	1.19 (0.58/2.43)
Suicide attempt
Age	0.40	0.09	19.83	<.001	1.49 (1.25/1.78)
Sex	−0.29	0.36	0.65	.42	0.75 (0.37/1.52)
Subjective health	0.35	0.27	1.70	.19	1.42 (0.84/2.39)
Respiratory, circulatory, blood	−0.94	0.74	1.59	.21	0.39 (0.09/1.68)
Digestive, genitourinary, endocrine, nutritional, metabolic	−0.27	0.65	0.18	.68	0.76 (0.22/2.70)
Nervous system, musculoskeletal, developmental	0.53	0.58	0.84	.36	1.70 (0.55/5.28)

Note. B = unstandardized beta value; SE = Standard errors of B; P = significance value; OR (95% CI) = odds ratios with 95% confidence intervals. The reference category is no suicidal ideation, plans or attempts.

Discussion

The present study used a nationally representative sample of adolescents aged 11–19 living in Northern Ireland to investigate whether having a CMC was associated with higher levels of depression, anxiety, and PTSD, as well as well as having had suicidal thoughts and plans, and having made a suicide attempt, above and beyond the influence of age, sex, and subjective health status. Just over one-quarter of participants (28%) had a CMC, positioning our findings at the upper end of global estimates, which vary between 20% and 30% (WHO, 2025a). Asthma was the most common CMC among participants, with a prevalence of 13.9%. This is slightly above the global estimate of approximately 11% (Yuan et al., 2025). Previous research has found that the Republic of Ireland and Northern Ireland have some of the highest prevalence rates of asthma in the world, where approximately 1 in 12 people suffer with asthma (Asthma Society of Ireland, 2024; Carthy et al., 2020). Given this context, the elevated proportion of those with a CMC in our sample is unsurprising, as asthma alone constituted almost 50% of all reported CMCs. A complex influence of gene-environment factors and interactions likely contributes to the development of asthma (Ogeyingbo et al., 2021), through air pollution, which is relatively poor in Ireland compared to most EU nations, has been hypothesized to contribute to asthma prevalence rates (Tang et al., 2020; Tiotiu et al., 2020).

It should be noted that 23% of children and adolescents living in Northern Ireland live in poverty, compared to 19% in the United Kingdom, and research indicates that poverty-driven health inequalities may be contributing to the higher prevalence of CMCs among youth (Royal College of Paediatrics and Child Health, 2020). It is well-established that adolescents who live in poverty are more likely to experience developmental delays, injuries, malnourishment, acute physical illnesses, and poor mental health, all of which can increase the likelihood of developing a CMC (Adjei, 2021). Northern Ireland also has the highest prevalence of mental disorders in the United Kingdom, which researchers partly attribute to a 30-year political conflict known as the Troubles (O’Neill & Rooney, 2018). Direct and familial experiences of this conflict have been shown to contribute to elevated levels of depression and PTSD in the Northern Irish general population (McLafferty et al., 2018).

Nevertheless, mean levels of depression and anxiety were low in the current sample and reflective of similar research in the general adolescent population in Europe and the United Kingdom (Baron et al., 2021; McKenzie et al., 2018). The mean PTSD score in our sample was low and indicative of mild PTSD symptom severity, based on qualitative descriptors of the ITQ-CA scoring system provided by Baker et al. (2025). Just under 8% of adolescents in this sample had thought about, planned, or attempted suicide. This frequency is lower than estimates from large-scale epidemiological studies, which report ranges from 10% to 20% for suicidal thoughts or plans, and from 4.6% to 16% for suicide attempts depending on the measurement methods employed and study setting (Van Meter et al., 2022; Zygo et al. (2018).

We hypothesized that all chronic illness classifications would be associated with poorer mental health and an increased risk of suicidal thoughts and plans, and attempts. Being female and having lower subjective health ratings were associated with higher levels of depression, anxiety, and PTSD, though age was not. Most of the variances in depression, anxiety, and PTSD were explained by the covariates, with CMC classifications only explaining 1–2% of additional variance in these scores. Subjective health was the variable most strongly associated with mental health difficulties, indicating that it is the perceived impacts on one’s health that are more problematic for adolescent wellbeing than the medical diagnoses themselves. This mirrors previous findings among adolescents (Balázs et al., 2018; Hetlevik et al., 2020), who reported diminished, but significant, effect sizes from CMCs when controlling for subjective health, and stronger effects for subjective health than CMCs. However, we observed several cases, particularly for depression and PTSD, where the effects of CMCs on mental health were rendered statistically non-significant. To our knowledge, no existing study has demonstrated this degree of attenuation of the effect of CMCs among adolescents, though the literature is sparse. Our findings suggest that subjective health may exert a stronger influence on adolescent mental health than previously recognized, at least across the CMC categories used in this study.

Notably, depression and anxiety were weakly associated with Nervous System, Musculoskeletal, and Developmental Diseases, as well as Digestive, Genitourinary, Endocrine, Nutritional, and Metabolic Diseases when controlling for subjective health, and PTSD was associated with Respiratory, Circulatory, and Blood Diseases. The effects we observed between these CMC classifications, depression, anxiety, and PTSD were small – smaller than in existing studies, although effects vary depending on sample, setting, and CMC diagnosis (Eckhoff et al., 2017; Marcev et al., 2024; Quek et al., 2017). These small effects of CMC on mental health variable, which persisted after age, sex, and subjective health were controlled for, may reflect the psychological burden of having a CMC, or they may reflect other mechanisms we did not control for in the current study. For instance, some research suggests that low self-esteem, peer exclusion, and perceived stigma act as mediators between depression and anxiety in adolescents with a CMC (Lacomba-Trejo et al., 2020). Future research could explore these mechanisms in more detail.

In contrast to the above, thinking about suicide or having a plan, and attempting suicide were only associated with increased age. Our findings contradict substantial existing evidence, which consistently identifies adolescents with CMCs as being significantly more likely to experience suicidal thoughts and attempts, and that CMCs constitute an independent risk factor for suicide completion (Iannucci & Nierenberg, 2021). Adolescents with co-occurring mental health difficulties and at least one CMC are considered to be especially vulnerable to suicide (Iannucci & Nierenberg, 2021; Stone et al., 2018). Nevertheless, our findings are consistent with a large body of research that has identified older adolescents as being particularly vulnerable to suicidal thoughts and attempts, with suicide mortality being at least 5 times greater among adolescents than pre-pubescent children (Hua et al., 2023). Ideation-to-action frameworks of suicide explain the transition from suicidal thoughts to attempts in a multistage process that is mediated through exposure to risk factors. These comprise victimization, negative perceptions of identity, thwarted sense of belonging or connectedness, suicide capability, and access to means (Kirshenbaum et al., 2024; Okado et al., 2021), factors we did not account for, but that those with a CMC have been identified as experiencing (Gamwell et al., 2018). Thinking about suicide or having a plan and having attempted suicide were most prevalent among those aged 16–19 years in this study (See supplementary materials for the distribution of suicidality across age).

The present study is not without limitations. Firstly, though the insights provided by the results are valuable for improving the understanding of the psychological difficulties experienced by a general population cohort of adolescents, they may not reflect clinical samples. Secondly, owing to the cross-sectional nature of the data, we cannot infer causality between variables or test mediation chains that may better explain the variances in the mental health variables and suicidality. Third, the short list of covariates included across each analysis means that potentially valuable contextual or individual-level factors were not accounted for. Finally, a methodological limitation of the Northern Ireland Youth Wellbeing study is that it excluded adolescents not living in non-private households (Bunting et al., 2022), for example, those who are homeless or in secure care. Findings do not generalize to these individuals.

Overall, the present study adds to the existing literature by identifying key factors associated with mental health difficulties and suicidality in adolescents. We demonstrated that subjective health showed stronger associations with depression, anxiety, and PTSD than diagnostic classifications of CMCs, with effect sizes stronger than previously identified across the literature. We also identified key CMC classifications that remained associated with depression and anxiety when controlling for subjective health status; these were “Digestive, genitourinary, endocrine, nutritional, and metabolic diseases” and “Nervous system, musculoskeletal, and developmental diseases.” PTSD was also associated with “Respiratory, circulatory, and blood diseases.” Thinking about suicide or having a plan, and having attempted suicide, were both associated with older age. Future research may wish to explore the potential psychosocial consequences associated with these CMC classifications that extend beyond subjective health status to better understand the links between CMCs and poorer mental health.

Footnotes

ORCID iD

Ilia Marcev

Ethical Considerations

No ethical approval was required for this study as it included data from previously published studies. No informed consent was needed as this study included data from participants who granted their informed consent.

Author Contributions

IM, PH, and JMP conceived and designed the research and analytic plan. PH sourced the dataset from the original investigators. IM conducted the statistical analyses. IM wrote the manuscript. PH and JMP revised the manuscript and made redrafts. JMP conducted the final review of the manuscript. All authors read and approved the manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Data available upon request from the corresponding author.*

Author Biographies

Ilia Marcev is currently a PhD candidate in the Psychology Department at Maynooth University. His research focuses on children and adolescents with chronic medical conditions and their mental wellbeing.

Joanna McHugh Power, PhD is an Associate Professor in Psychology at Maynooth University. Her research area is loneliness and social functioning in later life. She is a member of I-LINK (International Loneliness and Isolation Research Network), an international consortium of experts, the goal of which is to increase society’s ability through international collaboration to respond to loneliness throughout the life cycle by facilitating the sharing of knowledge and building of connections that will help improve the quality of research, policy, practice and overall understanding of loneliness.

Philip Hyland, PhD is a Professor in the Department of Psychology at Maynooth University. His research focuses on understanding the nature, predictors, and outcomes of psychological responses to trauma, and the dimensional structure of psychopathology. He currently serves as the Deputy Statistical Editor for the Journal of Traumatic Stress.

References

Adjei

N. K

, et al. (2021). Impact of poverty and family adversity on adolescent health: a multi-trajectory analysis using the UK Millennium Cohort Study. The Lancet Regional Health - Europe, 13, 100279. https://doi.org/10.1016/j.lanepe.2021.100279.

American Psychological Association . (2018). APA dictionary of psychology. Retrieved November 25, 2025, from. https://dictionary.apa.org/suicidality

Asher

Pearce

(2014). Global burden of asthma among children. International Journal of Tuberculosis & Lung Disease, 18(11), 1269–1278. https://doi.org/10.5588/ijtld.14.0170

Asthma Society of Ireland . (2024). Towards optimal asthma care: Research report on the challenges experienced by patients and stakeholders’ recommendations on improving severe asthma services. Retrieved November 28, 2025, from. https://www.asthma.ie/wp-content/uploads/2024/11/ASI-Towards_Optimal_Severe_Asthma_Care_in_Ireland_Report_2024.pdf

Baker

Smyth

Bartholomew

Buchanan

Hegarty

(2025). A review of the clinical utility and psychometric properties of the international trauma questionnaire – Child and adolescent version (ITQ-CA): Percentile rankings and qualitative descriptors. NovoPsych. https://novopsych.com/wp-content/uploads/2025/04/International-Trauma-Questionnaire-Child-and-Adolescent-Version-ITQ-CA-NovoPsych-Review-Paper.pdf

Balázs

Miklósi

Keresztény

Hoven

C. W.

Carli

Wasserman

Hadlaczky

Apter

Bobes

Brunner

Corcoran

Cosman

Haring

Kahn

Postuvan

Kaess

Varnik

Sarchiapone

Wasserman

(2018). Comorbidity of physical and anxiety symptoms in adolescent: Functional impairment, self-rated health and subjective well-being. International Journal of Environmental Research and Public Health, 15(8), 1698. https://doi.org/10.3390/ijerph15081698

Baron

Hurn

Ainger

Addlington

Shapiro

(2021). Revised Children’s anxiety and depression scale (RCADS): Psychometric properties in a clinical sample in the United Kingdom. Clinical Pediatrics, 6(186).

Bart

Ishak

W. W.

Ganjian

Jaffer

K. Y.

Abdelmesseh

Hanna

Gohar

Azar

Vanle

Dang

Danovitch

(2018). The assessment and measurement of wellness in the clinical medical setting: A systematic review. PubMed, 15(9–10), 14–23. https://pubmed.ncbi.nlm.nih.gov/30588362

Brady

A. M.

Deighton

Stansfeld

(2017). Psychiatric outcomes associated with chronic illness in adolescence: A systematic review. Journal of Adolescence, 59(1), 112–123. https://doi.org/10.1016/j.adolescence.2017.05.014

10.

Bunting

Nolan

McCartan

Davidson

Grant

Mulholland

Schubotz

McBride

Murphy

Shevlin

(2022). Prevalence and risk factors of mood and anxiety disorders in children and young people: Findings from the northern Ireland youth wellbeing survey. Clinical Child Psychology and Psychiatry, 27(3), 686–700. https://doi.org/10.1177/13591045221089841

11.

Carthy

Domhnaill

A. Ó.

O’Mahony

Nolan

Moriarty

Broderick

Hennessy

Donnelly

Naughton

Lyons

(2020). Local NO2 concentrations and asthma among over-50s in Ireland: A microdata analysis. International Journal of Epidemiology, 49(6), 1899–1908. https://doi.org/10.1093/ije/dyaa074

12.

Chorpita

B. F.

Yim

Moffitt

Umemoto

L. A.

Francis

S. E.

(2000). Assessment of symptoms of DSM-IV anxiety and depression in children: A revised child anxiety and depression scale. Behaviour Research and Therapy, 38(8), 835–855. https://doi.org/10.1016/s0005-7967(99)00130-8

13.

Cloitre

Shevlin

Brewin

C. R.

Bisson

J. I.

Roberts

N. P.

Maercker

Karatzias

Hyland

(2018). The international trauma questionnaire: Development of a self‐report measure of ICD‐11 PTSD and complex PTSD. Acta Psychiatrica Scandinavica, 138(6), 536–546. https://doi.org/10.1111/acps.12956

14.

Cobham

V. E.

Hickling

Kimball

Thomas

H. J.

Scott

J. G.

Middeldorp

C. M.

(2018). Systematic review: Anxiety in children and adolescents with chronic medical conditions. Journal of the American Academy of Child & Adolescent Psychiatry, 59(5), 595–618. https://doi.org/10.1016/j.jaac.2019.10.010

15.

Dalgleish

Black

Johnston

Bevan

(2020). Transdiagnostic approaches to mental health problems: Current status and future directions. Journal of Consulting and Clinical Psychology, 88(3), 179–195. https://doi.org/10.1037/ccp0000482

16.

Dudeney

Aaron

R. V.

Hathway

Bhattiprolu

Bisby

M. A.

McGill

L. S.

Gandy

Harte

Dear

B. F.

(2024). Anxiety and depression in youth with chronic pain. JAMA Pediatrics, 178(11), 1114–1123. https://doi.org/10.1001/jamapediatrics.2024.3039

17.

Eckhoff

Straume

Kvernmo

(2017). Multisite musculoskeletal pain in adolescence and later mental health disorders: A population-based registry study of Norwegian youth: The NAAHS cohort study. BMJ Open, 7(2), Article e012035. https://doi.org/10.1136/bmjopen-2016-012035

18.

Eskander

Vadukapuram

Zahid

Ashraf

Patel

R. S.

(2020). Post-traumatic stress disorder and suicidal behaviors in American adolescents: Analysis of 159,500 psychiatric hospitalizations. Cureus, 12(5), Article e8017. https://doi.org/10.7759/cureus.8017

19.

Ferro

M. A.

Rhodes

A. E.

Kimber

Duncan

Boyle

M. H.

Georgiades

Gonzalez

MacMillan

H. L.

(2017). Suicidal behaviour among adolescents and young adults with self-reported chronic illness. Canadian Journal of Psychiatry, 62(12), 845–853. https://doi.org/10.1177/0706743717727242

20.

Gamwell

K. L.

Baudino

M. N.

Bakula

D. M.

Sharkey

C. M.

Roberts

C. M.

Grunow

J. E.

Jacobs

N. J.

Gillaspy

S. R.

Mullins

L. L.

Chaney

J. M.

(2018). Perceived illness stigma, thwarted belongingness, and depressive symptoms in youth with inflammatory bowel disease (IBD). Inflammatory Bowel Diseases, 24(5), 960–965. https://doi.org/10.1093/ibd/izy011

21.

Hamplová

Klusáček

Mráček

(2022). Assessment of self-rated health: The relative importance of physiological, mental, and socioeconomic factors. PLoS One, 17(4), Article e0267115. https://doi.org/10.1371/journal.pone.0267115

22.

Hetlevik

Ø.

Meland

Hufthammer

K. O.

Breidablik

H. J.

Jahanlu

Vie

T. L.

(2020). Self-rated health in adolescence as a predictor of ‘multi-illness’ in early adulthood: A prospective registry-based Norwegian HUNT study. SSM - Population Health, 11, Article 100604. https://doi.org/10.1016/j.ssmph.2020.100604

23.

Heynemann

Thompson

Moncur

Silva

Jayawardana

Lewin

(2021). Risk factors associated with suicide in adolescents and young adults (AYA) with cancer. Cancer Medicine, 10(20), 7339–7346. https://doi.org/10.1002/cam4.4246

24.

G. W. K.

Liu

Karatzias

Hyland

Cloitre

Lueger-Schuster

Brewin

C. R.

Guo

Wang

Shevlin

(2022). Validation of the international trauma questionnaire—child and adolescent version (ITQ-CA) in a Chinese mental health service seeking adolescent sample. Child and Adolescent Psychiatry and Mental Health, 16(1), 66. https://doi.org/10.1186/s13034-022-00497-4

25.

Horn

Â. M.

Da Silva

K. A.

Patias

N. D.

(2021). School performance and symptoms of depression, anxiety, and stress in adolescents. Psicologia: Teoria e Pesquisa, 37, Article e372117. https://doi.org/10.1590/0102.3772e372117

26.

Hua

L. L.

Lee

Rahmandar

M. H.

Sigel

E. J.

Committee On Adolescence Council On Injury, Violence, And Poison Prevention . (2023). Suicide and suicide risk in adolescents. Pediatrics, 153(1), Article e2023064800. https://doi.org/10.1542/peds.2023-064800

27.

Iannucci

Nierenberg

(2021). Suicide and suicidality in children and adolescents with chronic illness: A systematic review. Aggression and Violent Behavior, 64, Article 101581. https://doi.org/10.1016/j.avb.2021.101581

28.

Kirshenbaum

J. S.

Pagliaccio

Bitran

Auerbach

R. P.

(2024). Why do adolescents attempt suicide? Insights from leading ideation-to-action suicide theories: A systematic review. Translational Psychiatry, 14(1), 266. https://doi.org/10.1038/s41398-024-02914-y

29.

Klonsky

E. D.

Dixon‐Luinenburg

May

A. M.

(2021). The critical distinction between suicidal ideation and suicide attempts. World Psychiatry, 20(3), 439–441. https://doi.org/10.1002/wps.20909

30.

Klonsky

E. D.

May

A. M.

(2015). The three-step theory (3ST): A new theory of suicide rooted in the “Ideation-to-Action” framework. International Journal of Cognitive Therapy, 8(2), 114–129. https://doi.org/10.1521/ijct.2015.8.2.114

31.

Lacomba-Trejo

Valero-Moreno

Montoya-Castilla

Pérez-Marín

(2020). Psychosocial factors and chronic illness as predictors for anxiety and depression in adolescence. Frontiers in Psychology, 11, 568941. https://doi.org/10.3389/fpsyg.2020.568941

32.

Levkovich

Yatzkar

Shenaar-Golan

(2025). Age and gender differences in emotional and behavioral functioning among youth referred to a psychiatric outpatient clinic at a public hospital. Children, 12(6), 683. https://doi.org/10.3390/children12060683

33.

Liu

Yang

Huang

Zhang

Guo

(2024). Thirty-year trends of anxiety disorders among adolescents based on the 2019 global burden of disease study. General Psychiatry, 37(2), Article e101288. https://doi.org/10.1136/gpsych-2023-101288

34.

Luo

Dashti

S. G.

Sawyer

S. M.

Vijayakumar

(2024). Pubertal hormones and mental health problems in children and adolescents: A systematic review of population-based studies. eClinicalMedicine, 76, Article 102828. https://doi.org/10.1016/j.eclinm.2024.102828

35.

Marcev

Lannon-Boran

Hyland

Power

J. M.

(2024). The factors associated with paediatric medical post-traumatic stress: A systematic review. Journal of Health Psychology, 30(11), 2860–2880. https://doi.org/10.1177/13591053241272214

36.

McKenzie

Murray

Freeston

Whelan

Rodgers

(2018). Validation of the revised Children’s anxiety and depression scales (RCADS) and RCADS short forms adapted for adults. Journal of Affective Disorders, 245, 200–204. https://doi.org/10.1016/j.jad.2018.10.362

37.

McLafferty

O’Neill

Murphy

Ferry

Bunting

(2018). The impact of childhood adversities on the development of Posttraumatic Stress Disorder (PTSD) in the Northern Ireland population. European Journal of Trauma & Dissociation, 3(2), 135–141. https://doi.org/10.1016/j.ejtd.2018.05.001

38.

Meentken

M. G.

Van Beynum

I. M.

Legerstee

J. S.

Helbing

W. A.

Utens

E. M. W. J.

(2017). Medically related post-traumatic stress in children and adolescents with congenital heart defects. Frontiers in Pediatrics, 5, 20. https://doi.org/10.3389/fped.2017.00020

39.

Miao

Jasim

Guha

Sluiter

Owen

K. B.

Yudianto

Lim

M. H.

Smith

B. J.

Manera

(2024). Experiences of loneliness and social isolation among young people with chronic physical conditions: A thematic synthesis of qualitative studies. Journal of Adolescence, 97(3), 593–608. https://doi.org/10.1002/jad.12445

40.

Miranda-Mendizabal

Castellví

Parés-Badell

Alayo

Almenara

Alonso

Blasco

M. J.

Cebrià

Gabilondo

Gili

Lagares

Piqueras

J. A.

Rodríguez-Jiménez

Rodríguez-Marín

Roca

Soto-Sanz

Vilagut

Alonso

(2019). Gender differences in suicidal behavior in adolescents and young adults: Systematic review and meta-analysis of longitudinal studies. International Journal of Public Health, 64(2), 265–283. https://doi.org/10.1007/s00038-018-1196-1

41.

Noyes

B. K.

Munoz

D. P.

Khalid-Khan

Brietzke

Booij

(2022). Is subthreshold depression in adolescence clinically relevant? Journal of Affective Disorders, 309, 123–130. https://doi.org/10.1016/j.jad.2022.04.067

42.

O’Connor

R. C.

(2011). The integrated motivational-volitional model of suicidal behavior. Crisis, 32(6), 295–298. https://doi.org/10.1027/0227-5910/a000120

43.

Ogeyingbo

O. D.

Ahmed

Gyawali

Venkatesan

Bhandari

Botleroo

R. A.

Kareem

Elshaikh

A. O.

(2021). The relationship between vitamin D and asthma exacerbation. Cureus, 13(8), Article e17279. https://doi.org/10.7759/cureus.17279

44.

Okado

Floyd

F. J.

Goebert

Sugimoto-Matsuda

Hayashi

(2021). Applying ideation-to-action theories to predict suicidal behavior among adolescents. Journal of Affective Disorders, 295, 1292–1300. https://doi.org/10.1016/j.jad.2021.08.137

45.

O’Neill

Rooney

(2018). Mental health in Northern Ireland: an urgent situation. The Lancet Psychiatry, 5(12), 965–966. https://doi.org/10.1016/s2215-0366(18)30392-4

46.

Osman

Bagge

C. L.

Gutierrez

P. M.

Konick

L. C.

Kopper

B. A.

Barrios

F. X.

(2001). The suicidal behaviors questionnaire-revised (SBQ-R):Validation with clinical and nonclinical samples. Assessment, 8(4), 443–454. https://doi.org/10.1177/107319110100800409

47.

Pfeifer

J. H.

Allen

N. B.

(2020). Puberty initiates cascading relationships between neurodevelopmental, social, and internalizing processes across adolescence. Biological Psychiatry, 89(2), 99–108. https://doi.org/10.1016/j.biopsych.2020.09.002

48.

Pinquart

(2018). Posttraumatic stress symptoms and disorders in children and adolescents with chronic physical illnesses: A meta-analysis. Journal of Child & Adolescent Trauma, 13(1), 1–10. https://doi.org/10.1007/s40653-018-0222-z

49.

Postigo-Zegarra

Schoeps

Pérez-Marín

Lacomba-Trejo

Valero-Moreno

(2024). Personal and family factors for emotional distress in adolescents with chronic disease. Frontiers in Psychology, 14, Article 1304683. https://doi.org/10.3389/fpsyg.2023.1304683

50.

Quek

Tam

W. W. S.

Zhang

M. W. B.

R. C. M.

(2017). Exploring the association between childhood and adolescent obesity and depression: A meta‐analysis. Obesity Reviews, 18(7), 742–754. https://doi.org/10.1111/obr.12535

51.

Royal College of Pediatrics and Child Health . (2020, March). Suicide - State of child health. RCPCH. Retrieved June 22, 2025, from. https://stateofchildhealth.rcpch.ac.uk/evidence/mental-health/suicide/#:∼:text=Across_the_UK%2C_the_suicide,own_lives_than_young_women

52.

Russo

(2022). Assessment and treatment of adolescents with chronic medical conditions. Journal of Health & Social Policy, 48(2), 69–78. https://doi.org/10.1007/s42843-022-00059-4

53.

Shi

Yan

Wang

Shen

(2022). Exploring the self-reported physical fitness and self-rated health, mental health disorders, and body satisfaction among Chinese adolescents: A cross-sectional study. Frontiers in Psychology, 13, Article 1003231. https://doi.org/10.3389/fpsyg.2022.1003231

54.

Stone

D. M.

Simon

T. R.

Fowler

K. A.

Kegler

S. R.

Yuan

Holland

K. M.

Ivey-Stephenson

A. Z.

Crosby

A. E.

(2018). Vital signs:trends in state suicide rates — United States, 1999–2016 and circumstances contributing to suicide — 27 states, 2015. MMWR Morbidity and Mortality Weekly Report, 67(22), 617–624. https://doi.org/10.15585/mmwr.mm6722a1

55.

Tang

McNabola

Misstear

(2020). The potential impacts of different traffic management strategies on air pollution and public health for a more sustainable city: A modelling case study from Dublin, Ireland. Sustainable Cities and Society, 60, Article 102229. https://doi.org/10.1016/j.scs.2020.102229

56.

Tiotiu

A. I.

Novakova

Nedeva

Chong-Neto

H. J.

Novakova

Steiropoulos

Kowal

(2020). Impact of air pollution on asthma outcomes. International Journal of Environmental Research and Public Health, 17(17), 6212. https://doi.org/10.3390/ijerph17176212

57.

Underner

Peiffer

Perriot

De Chazeron

Jaafari

(2022). Asthme et comportements suicidaires chez les adolescents: revue systématique. Revue des Maladies Respiratoires, 39(4), 344–366. https://doi.org/10.1016/j.rmr.2021.12.011

58.

Van Meter

A. R

Knowles

E. A

Mintz

E. H.

(2022). Systematic review and Meta-analysis: International prevalence of Suicidal ideation and Attempt in youth. Journal of the American Academy of Child & Adolescent Psychiatry, 62(9), 973–986. https://doi.org/10.1016/j.jaac.2022.07.867

59.

Van Orden

K. A.

Witte

T. K.

Cukrowicz

K. C.

Braithwaite

S. R.

Selby

E. A.

Joiner

T. E.

(2010). The interpersonal theory of suicide. Psychological Review, 117(2), 575–600. https://doi.org/10.1037/a0018697

60.

Wang

Toigo

Zutrauen

McFaull

S. R.

Thompson

(2023). Injuries among Canadian children and youth: An analysis using the 2019 Canadian health survey on children and youth. Health Promotion and Chronic Disease Prevention in Canada, 43(2), 98–102. https://doi.org/10.24095/hpcdp.43.2.05

61.

World Health Organization : WHO. (2025a, March 25). Suicide. https://www.who.int/news-room/fact-sheets/detail/suicide

62.

World Health Organisation . (2022). ICD-11: International classification of diseases (11th revision). https://icd.who.int/en/

63.

World Health Organization: WHO . (2025b, September 25). Noncommunicable diseases. https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases

64.

Wuorela

Lavonius

Salminen

Vahlberg

Viitanen

Viikari

(2020). Self-rated health and objective health status as predictors of all-cause mortality among older people: A prospective study with a 5-10-and 27-year follow-up. BMC Geriatrics, 20(1), Article 120. https://doi.org/10.1186/s12877-020-01516-9

65.

Yuan

Tao

Wang

She

Zou

Sun

Wei

Chen

Guo

Tian

Dong

Sun

Shang

, & Zhang

(2025). Global, regional, national burden of asthma from 1990 to 2021, with projections of incidence to 2050: A systematic analysis of the global burden of disease study 2021. eClinicalMedicine, 80, Article 103051. https://doi.org/10.1016/j.eclinm.2024.103051

66.

Zhang

Cheng

Choudhry

A. A.

Jiang

Pan

(2019). Suicidality among patients with asthma: A systematic review and meta-analysis. Journal of Affective Disorders, 256, 594–603. https://doi.org/10.1016/j.jad.2019.06.031

67.

Zygo

Pawłowska

Potembska

Dreher

Kapka-Skrzypczak

(2018). Prevalence and selected risk factors of suicidal ideation, suicidal tendencies and suicide attempts in young people aged 13–19 years. Annals of Agricultural and Environmental Medicine, 26(2), 329–336. https://doi.org/10.26444/aaem/93817

The Associations Between Chronic Illnesses,Mental Health,and Suicidality in Adolescence

Abstract

Objectives

Design

Methods

Results

Conclusions

Plain Language Summary

Keywords

Methods

Participants and Procedures

Inclusion Criteria for the Analytic Sample

Measures

Diagnosis of a CMC

Depression and Anxiety Symptoms

PTSD Symptoms

Indicators of Suicidality

Subjective Health Status

Data Analysis

Results

Descriptive Statistics

Hierarchical Multiple Regression Models of Depression, Anxiety, and PTSD

Multinomial Logistic Regression Model of Suicide Status

Discussion

Footnotes

ORCID iD

Ethical Considerations

Author Contributions

Funding

Declaration of Conflicting Interests

Data Availability Statement

Author Biographies

References