INTRODUCTION
Feeling safe is a fundamental contributor to wellbeing across all age groups. One significant source of insecurity is fear of crime (FOC), which is especially prevalent among older adults even though this group is statistically less likely to experience threats or violence. FOC has been linked to various adverse health outcomes, including depressive symptoms, lower life satisfaction, reduced physical functioning and limitations in daily activities.1-3) Sociodemographic factors, such as gender, are associated to FOC, with women typically experiencing higher prevalence. Moreover, FOC tends to increase with age, but few studies have examined variations in FOC within different older age groups.4,5)
Research on FOC has primarily originated in criminology and social science.6) FOC can be divided into affective, cognitive and behavioral components,4) with the behavioral component, such as avoiding outdoor activities in the evening, being particularly common among older adults.7) This avoidance could significantly affect engagement in health-promoting activities and in turn, health.1,2,5) While previous studies have examined the relationship between FOC and self-reported physical health and depressive symptoms, studies on different age groups among older adults or the relationship between FOC and total symptom burden remains limited.
A comprehensive assessment including various physical and mental symptoms is necessary to better understand the impact of FOC on health. As one of the first investigations, this cross-sectional population-based study aims to examine the associations between the behavioral component of FOC among previously not victimized older adults and symptom burden, where symptom burden is defined as the total number of symptoms and prevalence of different symptom domains.
MATERIALS AND METHODS
Study Population
This cross-sectional study is part of the Good Aging in Skåne (GÅS) project, a longitudinal general population-based study initiated in 2001 and part of the Swedish National Study on Aging and Care (SNAC).8) Detailed descriptions of the GÅS study have been published elsewhere.9)
The present study included participants from nine age cohorts (60, 66, 72, 78, 81, 84, 87, 90, 93 years), examined in four waves between 2001 and 2022, and were randomly selected from the Swedish population register. An invitational letter was sent to residents in five municipalities in Skåne County, southern Sweden, representing both urban and rural areas. Individuals were excluded if they were unreachable by mail or telephone, deceased prior to invitation, had language barriers, had emigrated from Skåne County, if data on fear of crime were missing, or if they had reported exposure to crime or threats during the last year. A flowchart of the inclusion process is provided in Fig. 1. The final sample comprised 5,832 participants, 3,170 (54.4%) women and 2,662 (45.6%) men.
Self-reported questionnaires were used to assess FOC, sociodemographic factors, lifestyle habits, and functional capacity measured as activities of daily living (ADL). Diseases were confirmed or diagnosed in a medical examination performed by a physician and the Swedish National Patient Registry was used to confirm participants’ health status. Assessments were conducted at the research clinic, or at home or via phone interviews for participants with health-related reasons.
Assessment of Fear of Crime
FOC was assessed using the question “Has it happened in the past year that you refrained from going out in the evening due to fear of being assaulted, robbed or molested?” This question reflects the behavioral component of FOC.7) Response options included “Never,” “Occasionally,” “Quite often,” “Often,” and “Very often.” The categories “Quite often,” “Often,” and “Very often” were combined into a single category, labelled “Often,” resulting in a variable with three response categories. It is essential to recognize that we measured the behavioral component of FOC by asking participants whether they would avoid going out in the evening due to the risk of being assaulted, robbed or molested. This means that the responses specifically reflect the fear of being subjected to violence or threats of violence and a behavioral avoidance as a consequence, rather than a FOC per se.10) It is in this sense that we use the term fear of crime (FOC) in the text below.
Assessment of Symptom Burden
Symptoms were assessed with the modified Gothenburg Quality of Life (GQoL) instrument, described by Tibblin et al.11) GQoL consists of 30 variables corresponding to mental and physical health and functioning. Participants were asked if they had experienced certain symptoms with four alternatives, ranging from “not at all” to “yes, a lot.” In line with previous studies, answers were dichotomized into “yes” if participants had experienced the symptom during the past three months or “no” if not experienced.12) This allowed for the construction of a continuous variable, ranging from 0 to 30 symptoms.
Symptoms were later grouped into seven domains: depressive, tension, gastrointestinal-urinary, musculoskeletal, metabolic, cardiopulmonary, and head symptoms.11) To be included in one or more domains of symptoms, participants needed to experience at least one symptom in the domain during the past three months.13)
Covariates
Sociodemographic and lifestyle factors
Sociodemographic factors included sex, age, education, cohabiting status, financial status, and place of residence. Men and women were analysed separately and to aid with interpretation, age was grouped into three categories: 60-year-olds, 70-year-olds and 80+-year-olds. Education was categorized into elementary school, secondary school (12 years of education) or university (12+ years of education). Cohabiting status was dichotomized into “cohabiting” or “single.” Financial difficulties were grouped into “yes” or “no,” based on the question “Has it been difficult to make ends meet for living expenses in the past year?” Place of residence was dichotomized into “rural” (countryside or small village) or “urban” (densely populated area or city center).14)
Physical activity was categorized into sedentary (not more than simple household tasks), lighter (walking, gardening, regular household work) and moderate to strenuous activities (more exhausting exercise, e.g., heavy household work, running, swimming, gymnastics or other sports).15) Alcohol consumption was categorized into “never,” “1-4 times per month,” and “>2 times per week.”14) Smoking status was grouped into “non-smoker,” “former smoker,” and “current smoker.”15)
Four waves of participants were recruited between the years 2001–2022. To reduce the risk that the timing of the various examinations would have a decisive influence on the FOC and further the overall result, adjustment was made for inclusion period by creating dummy variables where the first examination cohort was set as reference.
Health-related variables
Since underlying morbidities could influence the symptoms reported, various diseases were evaluated by the study physician, grouped under heart disease (myocardial infarction, angina pectoris, arrhythmia), hypertension, cerebrovascular disease (stroke, transient ischemic attack, reversible ischemic neurologic deficit), endocrine disease (diabetes type 1 or 2, thyroid disease), pulmonary disease (asthma, chronic obstructive pulmonary disease, tuberculosis), musculoskeletal disease (osteoporosis, arthrosis, inflammatory joint disease, hip fracture), and cancer (any type of malignant tumor). The number of morbidity categories were categorized as 0, 1, 2, or ≥3.
Dependence in ADL was assessed by the Katz ADL-index, evaluating the level of dependence in six basic activities (bathing, dressing, toileting, transferring, feeding, and continence).16) Based on the results, participants are grouped into one of seven categories with distinct levels of dependence. Due to low frequency of participants in the dependent groups, ADL was dichotomized into “independent” and “dependent” (dependent in 1–6 activities). The Katz ADL-index has shown validity and reliability in a Swedish setting.17)
Cognitive functioning was measured using the Mini Mental State Examination (MMSE) measuring global cognitive function. The scale ranges from 0–30 points and grouped into 0–24 points (representing severe to mild dementia) and 25–30 points (mild cognitive impairment to no cognitive impairment).18)
Depressive mood was assessed by behavioral scientist using the Montgomery-Åsberg Depression Rating Scale (MADRS) which includes 10 questions addressing anxiety, lack of initiative, sleep length and quality, reduced emotional involvement, suicidal thoughts et cetera. Each question is rated from 0–6 points.19) Participants were grouped by scores 0–6 (no depression) or 7–60 (depressed mood). The MADRS has been reported to be a reliable instrument detecting depression in non-demented older adults.20)
Ethics Approval and Consent to Participate
The study was conducted in accordance with the Declaration of The Code of Ethics of the World Medical Association (Declaration of Helsinki)21) and adhered to the ethical guidelines for authorship and publishing in the Annals of Geriatric Medicine and Research.22) Ethical approval was granted by the Regional Ethics Committee at Lund University (Registration No. LU 744-00). All participants in the GÅS study received information about the study and written consent was obtained.
Statistical Analysis
Population characteristics were presented in Table 1. Categorical variables (sociodemographics, lifestyle, health factors, symptom domains) were presented by absolute numbers and percentages and correlation analyses performed in relation to fear of crime using the Pearson chi-square (χ2) test (Tables 2, 3). Total symptom burden was assessed for normality using the Kolmogorov–Smirnov test and Q-Q plots. As the data were non-normally distributed, symptom counts were presented using medians and corresponding interquartile range (IQR), Q1–Q3, and compared across FOC levels using the Kruskal–Wallis test (Tables 2).
Multiple linear regression was used to examine the relationship between fear of crime and the total symptom count (Table 4), while multiple logistic regression analyzed the association between FOC and symptom domains (Tables 5). All the presented independent variables were simultaneously entered into the regression models, and all variables were entered as dummy variables.
Residuals in the linear model were normally distributed. No collinearity was detected; all variance inflation factors (VIFs) were <5.0.23) For logistic models, Hosmer–Lemeshow tests were non-significant, indicating acceptable model fit. A p-value of <0.05 was considered statistically significant. Analyses were performed using IBM SPSS Statistics version 30 (IBM, Armonk, NY, USA).
RESULTS
Description of the Study Sample
A total of 5,832 participants were included in the analysis of FOC and health (Fig. 1). Women comprised 54.4% of the sample. Overall, 34.7% of participants reported FOC at least occasionally during the last year (Table 1). Prevalence of FOC was higher among women and participants aged 70 years and older (Table 2). Specifically, 47.7% of women and 19.3% of men reported FOC. By age group, 26.9% of 60-year-olds, 46.2% of 70-year-olds, and 46.3% of participants aged 80 and above reported FOC. For both men and women, the prevalence of fear FOC was lower among those living in rural areas, had a higher education, was cohabitating, engaged in higher levels of physical activity, independent in ADL and did not suffer from a depressive mood or physical illness (Table 2).
Fear of Crime and Number of Reported Symptoms
Median number of symptoms for the whole study population ranged from 7 (IQR 4–12) in the group not experiencing FOC to 12 (IQR 8–17) in the group reporting FOC often (Table 2). For men, the number of symptoms ranged from 7 (IQR 3–11) in the group not experiencing FOC to 12 (IQR 7–16.5) in the group reporting FOC often. For women, the number of symptoms ranged from 8 (IQR 4–13) in the group not experiencing FOC to 12 (IQR 8–17) in the group reporting FOC often (Table 2). For both men and women, the proportion reporting FOC was highest among those who were 80 years old and above, living alone, living in an urban area, dependent in ADL, cognitive impaired, depressed and suffered from illness.
In the multiple linear regression model adjusted for sociodemographics, lifestyle, health factors and date of examination (i.e. included waves 1–4), FOC for both men and women was significantly associated with higher symptom counts (Table 4). For both men and women and compared to participants who never experience FOC, those reporting frequent FOC had approximately two more symptoms. No significant differences were found between the groups reporting FOC occasionally, often or often. In the adjusted regression model and among both men and women, financial difficulties, former smoking status, ADL dependence, cognitive functioning (MMSE ≤24) and previous illness were positively associated with symptom burden, while physical activity was inversely associated (Table 4).
Fear of crime and symptom domains
Across all symptom domains, the prevalence rates were higher in the groups reporting FOC compared to those without, with rates increasing alongside FOC frequency (Table 3). Among men reporting FOC often, prevalence ranged from 58.7% (gastrointestinal-urinary domain) to 85.3.1% (depressive domain), compared to 37.4% and 71.5%, respectively, in those without FOC. Among women reporting FOC often, prevalence ranged from 59.8% (gastrointestinal-urinary domain) to 92.5% (depressive domain), compared to 39.8% and 80.8.5%, respectively, in those without FOC.
In the adjusted multiple logistic regression models, men reporting FOC often was significantly associated with increased odds ratio (OR) in the depressive, tension, gastrointestinal-urinary, cardiopulmonary and head domains compared to those never reporting FOC (reference) (Table 5). Among women reporting FOC often, all symptom domains were associated with an increased OR compared to those never reporting FOC (reference).
For example, men reporting FOC very often had an OR of 1.71 (95% confidence interval [CI] 1.03–2.85) for the depressive domain and 1.05 (95% CI 1.20–2.37) for the gastrointestinal-urinary domain compared to those without FOC. Women reporting FOC very often had an OR of 2.25 (95% CI 1.61–3.15) for the depressive domain and 1.89 (95% CI 1.51–2.35) for the gastrointestinal-urinary domain compared to those without FOC.
DISCUSSION
To our knowledge, this is among the first study to examine total symptom burden and multiple health domains in relation to FOC. The overall prevalence of FOC was 34.7% (47.7% among women and 19.3% among men), consistent with a nationwide study of older adults aged 65-84 years old.24) Our results revealed a statistically significant association between FOC and total number of symptoms in men and women, adjusted for various sociodemographic and health factors. Individuals reporting FOC experience more symptoms, suggesting poorer health status. Although the associations between FOC and symptom burden were statistically significant, overlapping confidence intervals suggest that the symptom burden may not increase with higher levels of FOC. This points toward a threshold effect, where the mere presence of FOC, regardless of severity, may be most relevant.
High symptom burden is associated with a deteriorating health-related quality of life among older adults,25) and the symptoms are common reasons for people to seek healthcare26) One explanation is that FOC acts as a stressor with direct health impacts. Chronic stress contributes to the development and exacerbation of many disorders, including depression, migraine and fibromyalgia, all of which would result in a higher symptom burden.27,28) Dysregulation of the circadian rhythm of cortisol, leading to hyperactivity of the hypothalamic-pituitary-adrenal axis, may mediate these effects.29) Hamilton et al.,30) observed that psychological stress in adults, with a median age of 65, is associated with increased cortisol and inflammatory markers and linked to diseases such as cardiovascular disease.31) Whether FOC specifically affects cortisol rhythms is beyond this study’s scope. Additionally, FOC may lead to reduced participation in health-promoting activities, further affecting health.
The causal direction between FOC and health is not fully understood, with some studies indicating a bi-directional relationship.32,33) It would be unreasonable to claim that this cross-sectional study demonstrated a causal relationship, even though it might seem reasonable to think of symptom burden as a consequence of FOC, with less participation in health-promoting activities.1) At the same time, an increase in symptoms may lead to participants feeling more vulnerable. A vulnerability that can both lead to changed behaviours and at the same time to an increased fear of crime.
Other factors associated with FOC in our study included dependence in ADL, low levels of physical activity and cognitive impairment and number of morbidities, all factors which might make a person feel especially vulnerable. Studies arguing that FOC is a function of prior mental and physical health have measured FOC by participants’ frequency of fear or perceived risk of victimization, which may not show the same relationships as behavioral FOC.32-34)
Gender has been identified as the single most crucial factor in predicting fear of crime. Research consistently shows that women experience a higher degree of insecurity than men, despite men being statistically at greater risk of being victimized.35) This fear-gender gap has been explained, among other things, by women’s fear of sexual assault, that they have more difficulty physically defending themselves, and that they are socialized to be more cautious and fearful, and adopt roles as protectors and caregivers.36) However, regarding gender differences and FOC among older adults, our results are consistent with previous studies.24)
In the literature contrasting results have been shown regarding the effect of age on FOC.4,5) We found a significant difference in prevalence of FOC between the 60-year-olds (14.2%) and the 70/80+-year-olds (25.6.2% and 28.4%) men and between the 60-year-olds (38.7%) and the 70/80+-year-olds (62.7% and 59.3%) women. For both sexes, the difference could be explained by participants in the 60-year-old group to a higher rate were in better health, cohabitating and had higher levels of physical activity. Many people in Sweden aged 60–69 are still working,37) which also can contribute to this difference due to increased number of social contacts and hence reduced feeling of loneliness, which previously have been linked to FOC.1,2) In the linear regression model, no significant difference was found between different age groups in men and a significant but negative difference in women, suggesting that an increase in age itself does not necessarily impact the number of perceived symptoms.
We excluded 290 participants exposed to crime or threats of crime, as their fear can be said to be justified rather than anticipatory. Previous studies have not excluded this group, therefore not being able to dismiss the possibility that actual crime (rather than fear of it) is important for health.1) The question to address exposure to crime or threats of crime did not specify the place or setting of crime or threats. Participants who report this may have been victimized in their own home, with many studies acknowledging that violence at home is a big issue among elderly.24,38) Olofsson et al.24) found that 50% of elderly women who had been abused had been so in their own home. How this affects a person’s FOC is unknown, although both factors play a significant role for health outcomes.
Study Strengths and Weaknesses
This study has several strengths and weaknesses. Few studies have looked at different age groups among older adults in relation to FOC. This study consists of a large general study population, representing different cities, both urban and rural environments, different living arrangements and socioeconomic factors.
Although the question we asked concerned fear of going out in the evening with the risk of becoming a victim of crime, several other reasons such as physical and mental illness, may also contribute to such avoidant behaviour. In our regression models, we have attempted to take this into account by adjusting for cognitive impairment, depression, functional impairment, and illness.
It could be seen as a weakness that the operationalization of fear of crime in this study was based on whether participants refrain from going out in the evening due to concerns about violence or harassment. Participants thus responded to the fear of victimization and its consequences, rather than the fear of the crime itself. Although the boundary between these may be blurred, the distinction is not considered crucial for the purpose of the study. For most respondents, behavioral FOC likely encompasses both aspects, and for this study there is no reason to assume that one would affect symptom burden to a greater extent than the other.
One limitation is that we assessed FOC as an avoidance behavior using a single-item question. This may negatively affect construct validity, especially if participants have difficulty understanding the question. A shortcoming we tried to avoid by always having trained personnel were on hand to answer any ambiguities in the survey questions. In a study as extensive and time-consuming as the GÅS study, it may be an advantage to use a single-item question when appropriate.
Since participants were randomly invited based on age, and the study population does not represent the age distribution in Sweden, we should be careful to generalize the results to the elderly population in whole and rather look at the different age groups. Participants were randomly selected and to reduce selection bias, home visits or phone interviews were made when participants could not make it to the research facility and aid was given to participants with e.g. hearing or vision impairments. However, there still is risk for selection bias. People that choose to participate in epidemiologic studies are healthier and more socioeconomically favourable compared to nonparticipants.39) There is also a possibility that people with high levels of behavioral FOC decline participation. Therefore, it is possible that the noted prevalence of FOC is an underestimation of the true prevalence.
Participants were recruited between 2001 and 2022, something that risks introducing temporal confounding due changes in crime rate in Sweden,40) or increased interest in the media's reporting of crime, or other societal changes that may influence FOC such as economic conditions, housing planning, healthcare reforms or standard of living. To minimize any confounding effects related to the different time periods when the participants were included in the study. Adjustments for these periods (study waves 1–4) are done in the regression models. The association between FOC and symptom burden still proved to be significant for men and women, both in terms of number of symptoms and prevalence in the different symptom domains.
Conclusion
Among non-victimized older adults living in southern Sweden, 19.3% of men and 47.7% of women reported fear of going out in the evening due to FOC, at least occasionally. FOC, measured as an avoidance behaviour was associated with an increase in self-reported symptoms and increased ORs for different symptom domains. It seems to be the presence rather than the level of FOC affecting symptom burden. These findings highlight avoidance behaviour as a potential stressor adversely impacting older adults’ health, warranting attention in clinical and public health contexts. Addressing FOC as an avoidance behaviour may improve health outcomes. Interventions aimed at reducing this fear of going out in the evening with the risk of being subjected to violence could potentially lessen symptom burden and enhance well-being. Longitudinal studies are needed to clarify causal pathways and inform effective interventions.
PDF Links
PubReader
ePub Link
XML Download
Full text via DOI
Full text via PMC
Download Citation
