Fear of Crime During Years of Street Violence Is Associated With Worsening Cardiovascular Health Status

Abstract

Background:

Street violence has detrimental effects on cardiovascular health (CVH). However, the significance of these consequences have not been systematically evaluated. In this study, we aimed to assess the impact of fear of crime on CVH status among community-dwellers aged ≥40 years living in a rural village stricken by violence.

Methods:

Participants were selected from individuals enrolled in the Atahualpa Project Cohort, a population-based longitudinal study that aims to reduce the burden of cardiovascular risk factors and diseases in rural Ecuador. Fear of crime was evaluated using a structured scale. The Life’s Simple 7 construct of the American Heart Association was employed to assess CVH before the escalation of violence and crime in the village (2019) and at the end of the study (2024). Multivariate logistic regression models were fitted to examine the association between the exposure and outcomes.

Results:

A total of 648 individuals (mean age = 57.4 ± 11.7 years; 56% women) were included. At the end of the follow-up, significant association between fear of crime levels and worsening CVH status was noted. Participants allocated to the second and third tertiles of fear of crime were 3.27 (95% CI = 2.07-5.19) and 5.46 (95% CI = 3.14-9.48) times more likely to have worsening CVH status at follow-up compared to baseline determinations, respectively.

Conclusion:

This study shows an aggravating impact of fear of crime on the CVH status and identifies interventional targets that may help to reduce the risk of CVH status worsening in community-dwellers living in rural settings afflicted by violence.

Keywords

fear of crime street violence cardiovascular health status Life’s Simple 7 construct population-based cohort

Introduction

“Fear of crime” has been an important theme of theoretical and empirical inquiry in the field of criminology for more than 5 decades.^1,2 It has generally been assumed, and to a lesser extent corroborated, that fear of crime is associated with “poorer mental status, reduced physical functioning, and lower quality of life.”³ However, as Jackson and Stafford⁴ observed, “robust evidence on the link between worry about crime and health is surprisingly scarce.”Especially lacking are rigorous, longitudinal studies that quantify the impact of fear of crime on specific health outcomes and that demonstrate the direction of causality.

Perhaps the best-known longitudinal effort was the Whitehall II Study that followed more than 10,000 London-based civil servants, aged 33 to 55 years, over a 2-year period (2002-2004).³ The authors of that study concluded that the “curtailment of physical and social activities is a mediating pathway. . . resulting in an inverse association between fear of crime and subjective mental and physical health.” In this connection, it is notable that their index of physical health was a measurement of walking speed and lung function, which may implicate any number of health factors.

Of further relevance to the present study is the fact that most criminology research on fear of crime is concerned with urban crime. Rural crime has been largely neglected although there has been intermittent interest in other-than-urban crime, particularly since 2010.⁵ Moreover, the vast majority of research on fear of crime has taken place in the U.S. and the U.K.; more recently, there has been increased interest in this issue in the “Global South” which includes Latin America. As has been pointed out, “globalization, organized crime, ideological and other societal changes are reshaping criminogenic conditions in rural areas.”⁵ For these reasons, our focus on a community in rural Ecuador is of particular importance.

Ecuador has experienced a wave of street violence and criminal homicides during recent years. The official rate of criminal homicides in 2019 was 6.8/100 000 inhabitants, which increased to 43.94/100 000 in 2023 (https://es.statista.com/estadisticas/1402384/tase-de-homicidios-ecuador). This has been associated with an increased frequency of monetary extortions and kidnappings which increase the fear—in the population—of being a victim of crime. Fear of crime, in turn, has a negative impact on quality of life and, according to previous reports, may result in adverse effects on cardiovascular health (CVH) metrics.^6
-9 However, there remains a gap in longitudinal population studies that evaluate individuals both before and during a peak of violence to assess the association between fear of crime and the worsening of CVH metrics. This study aims to assess this association in community dwelling middle-aged and older adults living in a rural village in Santa Elena Province, Ecuador—one of the regions experiencing the highest rise in street violence within the country (https://www.teleamazonas.com/aumento-alarmante-de-la-delincuencia-en-la-provincia-de-santa-elena).

Methods

Study Population

We included community-dwellers aged ≥40 years identified by means of door-to-door surveys (2012-2019) and prospectively enrolled in the Atahualpa Project Cohort.¹⁰ These individuals have undergone regular follow-ups every 6 to 12 months, including periodic assessments of CVH status. Participants are relatively homogeneous regarding ethnicity (Amerindians), low levels of education, a low socio-economic status, and a diet rich in oily fish intake but poor in dairy products and red meat. In addition, a low migration rate and high retention in the Atahualpa Project Cohort provide optimal conditions for carrying out longitudinal studies in this population.¹¹ Individuals who agreed to sign informed consents at baseline and to participate in follow-up interviews were included.

Study Design

Baseline information on CVH metrics were obtained during the 2019 door-to-door survey (representing the timepoint before the subsequent escalation of violence and crime in the village) and in January 2024, when extortions, kidnappings, and homicides were at their peak. We then evaluated whether higher fear of crime levels were associated with worsening CVH status and individual metrics (see below). All participants signed a comprehensive informed consent before enrollment and the study was approved by a local Ethics Committee with international certifications.

Cardiovascular Health Status

We collected data on cardiovascular risk factors included in the Life’s Simple 7 construct of the American Heart Association.¹² This construct comprises 7 CVH metrics that include: smoking status, body mass index, physical activity, diet, blood pressure, fasting glucose, and total cholesterol blood levels. Each of these metrics was stratified as ideal, intermediate, or poor according to previously defined cutoffs (Table 1). The CVH status was classified according to the following parameters: “ideal,” when all metrics were in the ideal range; “intermediate,” when 1 or more metrics were in the intermediate range but with no poor metrics; and “poor,” when at least 1 metric was in the poor range. Worsening was defined as the change in CHV status and each of the 7 metrics (between baseline and follow-up) from ideal to intermediate/poor or from intermediate to poor.

Table 1.

Cardiovascular Health Metrics According to the Life’s Simple 7 Construct of the American Heart Association.

• Smoking: ideal (never or quit >1 year), intermediate (quit ≤1 year), and poor (current smoker).

• Body mass index: ideal (<25 kg/m²), intermediate (25-<30 kg/m²), and poor (≥30 kg/m²).

• Physical activity: ideal (≥150 min/week moderate intensity or ≥75 min/week vigorous intensity or equivalent combination), intermediate (1-149 min/week moderate intensity or 1-74 min/week vigorous intensity or equivalent combination), and poor (no moderate and vigorous activity).

• Diet: ideal (4-5 healthy components), intermediate (2-3 healthy components), and poor (0-1 healthy component); based on 5 health dietary components (≥4.5 cups fruits and vegetables/day, ≥two 3.5-oz servings fish/week, ≥three 1-oz equivalent servings fiber-rich whole grains/day, <1500 mg sodium/day, and ≤450 kcal sugar-sweetened beverages/week).

• Blood pressure: ideal (untreated and <120/<80 mmHg), intermediate (treated to <120/<80 mmHg or 120-139/80-89 mmHg), and poor (≥140/90 mmHg).

• Fasting glucose: ideal (untreated and <100 mg/dL), intermediate (treated to <100 mg/dL or 100-125/mg/dL), and poor (≥126 mg/dL).

• Total cholesterol: ideal (untreated and <200 mg/dL), intermediate (treated to <200 mg/dL or 200-239 mg/dL), and poor (≥240 mg/dL).

Fear of Crime

We collected data of fear of crime by the use of a recently introduced field instrument that includes 4 key items rated on a Likert scale: (1) how fearful are you of crime in your village, ranging from 1 (not fearful at all) to 4 (very fearful); (2) how do you perceive the crime rate in your village compared to neighboring villages, ranging from 1 (very low) to 3 (about the same) to 5 (very high); (3) how dangerous or safe it is to walk in your village during the daytime, ranging from 1 (completely safe) to 4 (extremely dangerous); and (4) how dangerous or safe it is to walk in your village after dark, ranging from 1 (completely safe) to 4 (extremely dangerous).¹³ This questionnaire has a minimum score of 4 points and a maximum of 17, with higher scores indicating a greater fear of crime.

Statistical Analysis

Data analyses were carried out using STATA version 18 (College Station, TX, USA). In unadjusted analyses, continuous variables were compared by linear models and categorical variables by the chi-square or Fisher exact test as appropriate. Worsening in CVH status as well as in each of the CVH metrics were used as distinct dependent variables (outcomes) and the score on the fear of crime scale stratified in tertiles (exposure) was used as the independent variable. Separate multivariate linear regression models were fitted to assess the association between the exposure and the outcomes, after adjusting for age, sex, and levels of education.

Results

A total of 773 individuals aged ≥40 years (enrolled from 2012 to 2019) were actively enrolled in the Atahualpa Project Cohort up to June 2019 and received baseline interviews (see above). At the end of the observation period (January 2024), 663 participants received follow-up interviews as they were still active in the cohort and were able to walk without assistance. Fifteen of these subjects had incomplete clinical forms and were excluded from analysis.

At baseline, the mean age of the 648 participants was 57.4 ± 11.7 years, 363 (56%) were women, and 321 (49%) had elementary school education only. At baseline, 11 (2%) participants had an ideal, 216 (33%) had an intermediate, and 421 (65%) had a poor CVH status. At follow-up, there were no participants with an ideal CVH status, 114 (18%) had an intermediate, and 534 (82%) had a poor status. Overall, 431 individuals had a similar CVH status at baseline and follow-up (67%), 51 (8%) had a better CVH status, and the remaining 166 (26%) had a worse CVH status. The mean (±SD) score in the fear of crime questionnaire in the 648 participants was 7 ± 1.7 points, which differed across individuals with worse CVH status at follow-up compared to those with a similar/better CVH status (7.7 ± 1.6 vs 6.8 ± 1.7 points; P < .001). When individual CVH metrics were analyzed separately, we noted worsening in all metrics at follow-up, the most notable being diet, fasting glucose, and arterial blood pressure; however, worsening was associated with higher levels of fear of crime only for body mass index and physical activity (Table 2).

Table 2.

Association Between Fear of Crime Scores (Mean ± SD) and Progression of Individual Cardiovascular Health Metrics at Follow-up in Participants of this Study.

CVH metric	Metrics status at follow-up	Fear of crime scores	P value
Smoking	Similar/better (n = 624)	7 ± 1.7	.257
Smoking	Worse (n = 24)	7.4 ± 1.6	.257
Body mass index	Similar/better (n = 536)	6.9 ± 1.6	.020^a
Body mass index	Worse (n = 112)	7.3 ± 1.9	.020^a
Physical activity	Similar/better (n = 540)	6.9 ± 1.7	.006^a
Physical activity	Worse (n = 108)	7.4 ± 1.8	.006^a
Diet	Similar/better (n = 308)	6.9 ± 1.7	.135
Diet	Worse (n = 340)	7.1 ± 1.7	.135
Blood pressure	Similar/better (n = 405)	6.9 ± 1.6	.142
Blood pressure	Worse (n = 243)	7.1 ± 1.8	.142
Fasting glucose	Similar/better (n = 380)	6.9 ± 1.8	.145
Fasting glucose	Worse (n = 268)	7.1 ± 1.6	.145
Total cholesterol	Similar/better (n = 465)	6.9 ± 1.7	.171
Total cholesterol	Worse (n = 183)	7.1 ± 1.6	.171

Statistically significant result.

A multivariate logistic regression model showed a significant association between levels of fear of crime stratified in tertiles (4-6, 7-8, and 9 or more points) and worsening CVH status, when the second (OR = 3.27; 95% CI = 2.07-5.19) and the third tertiles (OR = 5.46; 95% CI = 3.14-9.48) were compared with the first tertile (referent value); being male remained independently significant in this model (Table 3). Separately multivariate models using individual CVH metrics as the dependent variables showed significant associations between levels of fear of crime and worsening body mass index and physical activity (Table 4).

Table 3.

Multivariate Logistic Regression Model Showing Significant Associations Between Fear of Crime Levels and Worsening of Cardiovascular Health Status at Follow-up.

Worsening CVH	Odds ratio	95% confidence interval	P value
First tertile fear of crime	Referent value
Second tertile fear of crime	3.27	2.07-5.19	<.001^a
Third tertile fear of crime	5.46	3.14-9.48	<.001^a
Age	0.99	0.97-1.00	.120
Being female	0.62	0.42-0.90	.013^a
Primary school	0.77	0.51-1.16	.213

Statistically significant result.

Table 4.

Separate Multivariate Logistic Regression Models Showing Associations Between Fear of Crime Levels and Worsening of Each of the 7 Cardiovascular Health Metrics at Follow-up.

Worsening smoking	Odds ratio	95% confidence interval	P value
First tertile fear of crime	Referent value
Second tertile fear of crime	1.05	0.42-2.63	.918
Third tertile fear of crime	1.30	0.38-4.46	.676
Worsening body mass index
First tertile fear of crime	Referent value
Second tertile fear of crime	1.14	0.71-1.83	.585
Third tertile fear of crime	1.90	1.08-3.36	.026^a
Worsening physical activity
First tertile fear of crime	Referent value
Second tertile fear of crime	1.36	0.83-2.25	.224
Third tertile fear of crime	2.06	1.13-3.77	.019^a
Worsening diet
First tertile fear of crime	Referent value
Second tertile fear of crime	1.33	0.94-1.88	.111
Third tertile fear of crime	1.39	0.87-2.20	.170
Worsening blood pressure
First tertile fear of crime	Referent value
Second tertile fear of crime	1.10	0.77-1.58	.604
Third tertile fear of crime	1.47	0.92-2.36	.107
Worsening fasting glucose
First tertile fear of crime	Referent value
Second tertile fear of crime	0.97	0.67-1.40	.873
Third tertile fear of crime	1.17	0.73-1.90	.512
Worsening total cholesterol
First tertile fear of crime	Referent value
Second tertile fear of crime	1.44	0.97-2.12	.067
Third tertile fear of crime	1.31	0.78-2.21	.304

All models were adjusted for age, sex, and levels of education. Significant results are marked with an (^a).

Discussion

This study underscores the detrimental impact of fear of crime on CVH status in middle-aged and older adults living in a rural setting of a country that has been afflicted by increasing street violence and criminal homicides. Fear of crime consistently correlated with worsening CVH across individual metrics with a particularly notable impact on increased body mass index and reduced physical activity.

It is possible that age and other factors previously reported in this cohort may have contributed to the detrimental effects observed in other CVH metrics.¹⁴ Nevertheless, the contributory effect of fear of crime on this association cannot be entirely dismissed as results from different models show a direct—though non-significant—association between fear of crime and higher levels of blood pressure and other CVH metrics.

The question of direction of causality has been raised in the past given that individuals with poor mental health may feel more unsafe and vulnerable.¹⁵ Such observations led to hypothesize that poor health leads to increased worry about crime, but the results of the present study support the longitudinal adverse impact of fear of crime on cardiovascular health status.⁴

Our study concurs with the independent association between higher levels of fear of crime and selected CVH metrics (body mass index and physical activity) reported by some investigators.^7,8 However, it shows discrepancies regarding the association between fear of crime and worsening blood pressure as observed by others.^6,9 This could be related to the continuous efforts of our field personnel to enhance understanding of the deleterious effects of high blood pressure and the importance of the use of antihypertensive medications in participants with arterial hypertension. The same may apply to other risk factors measured in the Life’s Simple 7 construct, such as diet and fasting glucose.

Although increasing violence and crime represents a global challenge, its emotional and health impact may vary significantly across populations. This impact is likely influenced by cultural factors and socioeconomic status. In our study, participants exhibits homogeneous socioeconomic characteristics and being female appeared as an independently significant confounder. Nevertheless, it is important to note that our findings may not fully apply to other populations. Healthy behaviors such as physical activity and body weight control have shown to be pillars of CVH status in our rural community and have compared favorably to urban areas in developed countries.¹⁶ Therefore, our findings suggest that fear of crime poses a significant threat to healthy behaviors in our rural population.

The present study has limitations. The perception of being at risk for violence may be greater than the actual risk. This perception may be augmented by social media with its disproportionate coverage of violent news. In addition, there is the potential confounding impact of COVID-19 on well-being and cardiovascular risk factors. Our group has published on the morbidity of the SARS-CoV-2 pandemic in this community, but the additive effects on subsequent worsening of cardiovascular risk factors are difficult to calibrate.¹⁷ Nevertheless, the trajectory of escalating violence in the community was already evident well before this pandemic. There is also the possibility that unexplored confounders may have played a role in the impact of fear of crime on worsening CVH status. These limitations are offset by the population-based design and the unbiased enrollment of participants, the use of reliable field instrument to assess fear of crime as well as CVH metrics, and the homogeneity of the study population in terms of levels of education, lifestyles, income status, and living conditions. These similarities reduce the bias related to latent variables.

Conclusion

In conclusion, the present study shows a significant aggravating impact of fear of crime on the CVH status and on selected CVH metrics in the study population. This study highlights the crucial need for continuous education and campaigns aimed at promoting CVH amidst rising insecurity and crime. These interventions should focus on vulnerable individuals who are likely to be the most affected by street violence. Hopefully, recently introduced governmental policies aimed at reducing street violence will diminish the fear of crime and its impact on the CVH status of the population (https://www.eluniverso.com/noticias/politica/plan-de-seguridad-fenix-daniel-noboa-nota/).

Footnotes

Acknowledgements

We appreciate the continuous support of field personnel of the Atahualpa Project cohort.

Author Contributions

OHD: study design, manuscript drafting; RMM: statistical analysis, significant intellectual contribution to manuscript content; VJR: contributed to study design, significant intellectual contribution to manuscript content; DAR: study coordinator, data curation; EEA: data collection and analysis; MJS: manuscript drafting, significant intellectual contribution to manuscript content.

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Universidad Espíritu Santo—Ecuador. The sponsor had no role in the design of the study, in the collection, analysis and interpretation of data, or in the decision to submit the manuscript for publication.

Ethical Approval

The study was approved by the Ethics Committee of Hospital-Clínica Kennedy, Guayaquil (FWA 00030727). Research was conducted following the ethical principles of the Declaration of Helsinki.

Data Availability Statement

Aggregated data will be available upon reasonable request to the corresponding author.

ORCID iDs

Oscar H. Del Brutto

Denisse A. Rumbea

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