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The association between neighbourhood characteristics and physical victimisation in men and women with mental disorders.

ABSTRACT: BACKGROUND:How neighbourhood characteristics affect the physical safety of people with mental illness is unclear. AIMS:To examine neighbourhood effects on physical victimisation towards people using mental health services. METHOD:We developed and evaluated a machine-learning-derived free-text-based natural language processing (NLP) algorithm to ascertain clinical text referring to physical victimisation. This was applied to records on all patients attending National Health Service mental health services in Southeast London. Sociodemographic and clinical data, and diagnostic information on use of acute hospital care (from Hospital Episode Statistics, linked to Clinical Record Interactive Search), were collected in this group, defined as 'cases' and concurrently sampled controls. Multilevel logistic regression models estimated associations (odds ratios, ORs) between neighbourhood-level fragmentation, crime, income deprivation, and population density and physical victimisation. RESULTS:Based on a human-rated gold standard, the NLP algorithm had a positive predictive value of 0.92 and sensitivity of 0.98 for (clinically recorded) physical victimisation. A 1 s.d. increase in neighbourhood crime was accompanied by a 7% increase in odds of physical victimisation in women and an 13% increase in men (adjusted OR (aOR) for women: 1.07, 95% CI 1.01-1.14, aOR for men: 1.13, 95% CI 1.06-1.21, P for gender interaction, 0.218). Although small, adjusted associations for neighbourhood fragmentation appeared greater in magnitude for women (aOR = 1.05, 95% CI 1.01-1.11) than men, where this association was not statistically significant (aOR = 1.00, 95% CI 0.95-1.04, P for gender interaction, 0.096). Neighbourhood income deprivation was associated with victimisation in men and women with similar magnitudes of association. CONCLUSIONS:Neighbourhood factors influencing safety, as well as individual characteristics including gender, may be relevant to understanding pathways to physical victimisation towards people with mental illness.

SUBMITTER: Bhavsar V

PROVIDER: S-EPMC7443921 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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The association between neighbourhood characteristics and physical victimisation in men and women with mental disorders.

Bhavsar Vishal V Sanyal Jyoti J Patel Rashmi R Shetty Hitesh H Velupillai Sumithra S Stewart Robert R Broadbent Matthew M MacCabe James H JH Das-Munshi Jayati J Howard Louise M LM

BJPsych open 20200716 4

<h4>Background</h4>How neighbourhood characteristics affect the physical safety of people with mental illness is unclear.<h4>Aims</h4>To examine neighbourhood effects on physical victimisation towards people using mental health services.<h4>Method</h4>We developed and evaluated a machine-learning-derived free-text-based natural language processing (NLP) algorithm to ascertain clinical text referring to physical victimisation. This was applied to records on all patients attending National Health ...[more]

PMID: 32669154

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Project description:ObjectivesThe rapid growth of urban areas in China in the past few decades has introduced profound changes in family structure and income distribution that could plausibly affect mental health. Although multilevel studies of the influence of area-level socioeconomic factors on mental health have become more common in other parts of the world, a study of this sort has not been carried out in Chinese cities. Our objectives were to examine the associations of two key neighbourhood-level variables-median income and percentage of married individuals living in the neighbourhood-with mental disorders net of individual-level income and marital status in three Chinese cities.SettingHousehold interviews in Beijing, Shanghai and Shenzhen, PRC, as part of the cross-sectional World Mental Health Surveys.Participants4072 men and women aged 18-88 years.Primary and secondary outcome measuresLifetime and past-year internalising and externalising mental disorders.ResultsEach one-point increase in neighbourhood-level percentage of married residents was associated with a 1% lower odds of lifetime (p=0.024) and 2% lower odds of past-year (p=0.008) individual-level externalising disorder, net of individual-level marital status. When split into tertiles, individuals living in neighbourhoods in the top tertile of percentage of married residents had 54% lower odds of a past-year externalising disorder (OR=0.46, 95%?CI: 0.24 to 0.87) compared with those in the bottom tertile. Neighbourhood-level marital status was not statistically associated with either lifetime or past-year internalising disorders. Neighbourhood-level income was not statistically associated with odds of either internalising or externalising disorders.ConclusionsThe proportion of married residents in respondents' neighbourhoods was significantly inversely associated with having externalising mental disorders in this sample of Chinese cities. Possible mechanisms for this finding are discussed and related to social causation, social selection and social control theories. Future work should examine these relationships longitudinally.

Project description:BACKGROUND:Women Veterans have high rates of mental health disorders and other psychosocial factors which may render this population particularly vulnerable to negative health outcomes associated with unintended pregnancy. OBJECTIVE:The objective of our study was to assess the relationship between self-reported mental illness and history of unintended pregnancy among women Veterans. DESIGN AND PARTICIPANTS:Data are from a nationally representative, cross-sectional telephone survey of women Veterans, ages 18-45, who used VA for primary care within 12 months prior to interview (survey completion rate 83%). MAIN MEASURES:Predictors were self-report of any and number of mental health disorders (depression, anxiety, post-traumatic stress disorder, bipolar disorder, or schizophrenia). Outcomes were any and number of unintended pregnancies. Multivariable logistic and negative binomial regression were used to assess relationships between mental illness and unintended pregnancy. To assess women's current risk of unintended pregnancy, we examined associations between any mental health disorder and contraceptive use at last sex among heterosexually active women not desiring pregnancy. KEY RESULTS:Among 2297 women Veterans, 1580 (68.8%) reported a history of at least one mental health disorder, with 20.1, 21.6, and 27.0% reporting one, two, or three or more conditions, respectively. Any history of unintended pregnancy was reported by 1315 women (57.3%); 28.3% reported one, 15.6% reported two, and 13.4% reported three or more. Compared to women with no mental illness, women with any mental health disorder were more likely to report any unintended pregnancy (60.3 vs. 50.5%; adjusted OR 1.40; 95% CI 1.15, 1.71) and to have experienced greater numbers of unintended pregnancies (adjusted incidence rate ratio 1.29; 95% CI 1.15, 1.44). Increasing numbers of mental health disorders were associated with greater numbers of unintended pregnancies. Contraceptive use and method efficacy at last sex did not differ by mental health status. CONCLUSIONS:Women Veterans with mental health disorders are more likely to have experienced any and greater numbers of unintended pregnancies than Veterans without mental health disorders.

Project description:BACKGROUND:Persons with mental disorders are at a higher risk than the general population for the subsequent development of certain medical conditions. METHODS:We used a population-based cohort from Danish national registries that included data on more than 5.9 million persons born in Denmark from 1900 through 2015 and followed them from 2000 through 2016, for a total of 83.9 million person-years. We assessed 10 broad types of mental disorders and 9 broad categories of medical conditions (which encompassed 31 specific conditions). We used Cox regression models to calculate overall hazard ratios and time-dependent hazard ratios for pairs of mental disorders and medical conditions, after adjustment for age, sex, calendar time, and previous mental disorders. Absolute risks were estimated with the use of competing-risks survival analyses. RESULTS:A total of 698,874 of 5,940,299 persons (11.8%) were identified as having a mental disorder. The median age of the total population was 32.1 years at entry into the cohort and 48.7 years at the time of the last follow-up. Persons with a mental disorder had a higher risk than those without such disorders with respect to 76 of 90 pairs of mental disorders and medical conditions. The median hazard ratio for an association between a mental disorder and a medical condition was 1.37. The lowest hazard ratio was 0.82 for organic mental disorders and the broad category of cancer (95% confidence interval [CI], 0.80 to 0.84), and the highest was 3.62 for eating disorders and urogenital conditions (95% CI, 3.11 to 4.22). Several specific pairs showed a reduced risk (e.g., schizophrenia and musculoskeletal conditions). Risks varied according to the time since the diagnosis of a mental disorder. The absolute risk of a medical condition within 15 years after a mental disorder was diagnosed varied from 0.6% for a urogenital condition among persons with a developmental disorder to 54.1% for a circulatory disorder among those with an organic mental disorder. CONCLUSIONS:Most mental disorders were associated with an increased risk of a subsequent medical condition; hazard ratios ranged from 0.82 to 3.62 and varied according to the time since the diagnosis of the mental disorder. (Funded by the Danish National Research Foundation and others; COMO-GMC ClinicalTrials.gov number, NCT03847753.).

Dataset Information

The association between neighbourhood characteristics and physical victimisation in men and women with mental disorders.

Publications

The association between neighbourhood characteristics and physical victimisation in men and women with mental disorders.

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