2020
DOI: 10.1007/s10865-020-00176-9
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Recent trends in the rural–urban suicide disparity among veterans using VA health care

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Cited by 38 publications
(42 citation statements)
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“…The majority used data of a cross-sectional nature [ 30 , 31 , 32 , 33 , 34 ]. Because the suicide rates were usually based on administrative databases (e.g., death registers) covering the entire population, and given that privacy needed to be guaranteed, ecological designs were often applied [ 35 , 36 ]; other designs were scarce (e.g., cohort design [ 37 ]). The year of publication of the included articles covered the period 1977–2020.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The majority used data of a cross-sectional nature [ 30 , 31 , 32 , 33 , 34 ]. Because the suicide rates were usually based on administrative databases (e.g., death registers) covering the entire population, and given that privacy needed to be guaranteed, ecological designs were often applied [ 35 , 36 ]; other designs were scarce (e.g., cohort design [ 37 ]). The year of publication of the included articles covered the period 1977–2020.…”
Section: Resultsmentioning
confidence: 99%
“…Pesonen et al focused on Finnish males in the 1980s and 1990s, but could not confirm significant geographic inequalities in suicide mortality for eastern Finland (though rates for the countryside were higher) with regionally diverging rates (e.g., a decline in urban areas) [ 38 ]. Congruent with suicide rates (2003–2017) for U.S. Veterans Affairs patients [ 37 ], no significant differences were observable in Australian urban and rural suicide rates (1986–1990) [ 41 ]. Others did not find urban–rural differences [ 30 , 44 , 49 , 51 ].…”
Section: Resultsmentioning
confidence: 99%
“…Physical and mental health comorbidities were assessed in the 2 years prior to date of admission using published bins of related ICD-9 14 and ICD-10 codes. 13 , 16 For mental health comorbidities, we coded the number of Diagnostic and Statistical Manual of Mental Disorders (5th edition) (DSM-5) categories (0–1, 2–3 and ≥4). 17 For physical health comorbidities, we coded diagnoses based on the number of Elixhauser conditions (0, 1, and ≥2).…”
Section: Methodsmentioning
confidence: 99%
“…We determined zip code of residence annually and relied on the Rural-Urban Commuting Area (RUCA) classification scheme to define RUCA codes 1–3 as urban and all others as rural. 16,20 Finally, we separated year of admission into four time periods (2003–2007, 2008–2011, 2012–2015 and 2016–2019) in order to adjust for and evaluate temporal trends.…”
Section: Methodsmentioning
confidence: 99%
“…From the CDW, we abstracted the following covariates: age, sex, race/ethnicity (Black, non-Black Hispanic, White, other), marital status at time of admission, primary discharge diagnosis, year of admission, and preadmission mental and physical health diagnoses over the 2 years before admission coded using a previously developed index (Shiner et al, 2021). We categorized primary discharge diagnosis using the following groupings: alcohol use disorders, bipolar disorders, depressive disorders, drug use disorders, psychotic disorders, trauma-related disorders, and other mental health disorders.…”
Section: Study Variablesmentioning
confidence: 99%