Sex- and age-specific trends in mortality from suicide and undetermined death in Germany 1991–2002

BACKGROUND: Over the last decade, significant downward linear time trends in suicide mortality were observed in most Western countries. To date, it is not established whether those favourable time trends developed homogeneously for sex and age groups and how they were affected by the number of undetermined deaths. METHODS: Data on suicide mortality and undetermined death from 1991 to 2002 in Germany were obtained from the German Federal Statistical Office. For each year, the age-standardised suicide rate (SR), undetermined death rate (UDR) and total rate (SR+UDR) was calculated by direct standardisation separately for men and women. Time trends were analyzed by Poisson regression estimating the average annual percentage change (AAPC) of the rates for sex and four age groups (15–24, 25–44, 45–74, ≥ 75 years). RESULTS: A significant decline of the SR was observed in all age groups but was less pronounced among the younger ages, particularly among men aged 15–24 years (AAPC -0.7%, p = 0.041). The SR in the oldest male age group (≥ 75 years) declined much stronger (AAPC -3.5%, p < 0.001). In women, the AAPC of the SR ranged from -1.7% to -4.6%. The average annual percentage changes in the age groups 25 – 74 years did not differ substantially for SR and SR+UDR. In contrast, due to an increase of undetermined deaths for subjects ≥ 75 years, time trends in this age group were affected by the number of undetermined deaths, especially in women. CONCLUSION: Observing downward trends in suicide mortality with lower declines for younger subjects, prevention strategies should focus in particular on younger subjects

Association between mortality from suicide in England and antidepressant prescribing: an ecological study

BACKGROUND: Antidepressant prescribing has been increasing in England. Studies in other countries suggest that while this may be associated with reduced suicide rates, it may also be associated with increased fatal poisoning from antidepressant drugs. We therefore conducted an ecological study to assess the association between prescription rates for antidepressants and suicide or fatal antidepressant-related poisoning in England. METHODS: The Office for National Statistics provided information on the number of suicides, antidepressant-related poisoning deaths and populations for England between 1993 and 2002. The Department of Health supplied data on prescriptions for all antidepressants dispensed in England. Associations between prescriptions and deaths were assessed using Spearman's rank correlation coefficient. RESULTS: There were 46,747 suicides, 3,987 deaths involving tricyclic antidepressants and 430 involving selective serotonin re-uptake inhibitors and other antidepressants. Increased antidepressant prescribing was statistically associated with a fall in suicide rates (Spearman's r(s )= -0.73, p = 0.02) and fatal poisoning involving tricyclic antidepressants (r(s )= -0.64, p = 0.05). In contrast, increased prescribing of selective serotonin re-uptake inhibitors and other antidepressants was statistically associated with an increase in fatal poisoning involving these drugs (r(s )= 0.99, p < 0.001). CONCLUSION: Increased prescribing of antidepressants may indicate improved diagnosis and treatment of depression in primary care. Our analysis suggests that this was accompanied by lower suicide rates. A decrease in poisoning deaths involving tricyclic antidepressants may suggest a change in preference for using serotonin reuptake inhibitors and other antidepressant drugs for high-risk patients. This may also partially explain the increase in deaths involving these drugs. Due to the ecological nature of the design, we cannot say conclusively whether reduced suicide rates are a direct consequence of increased antidepressant prescribing rates. To confirm these associations, individual level data on prescribing and suicide is needed

Using routine data to monitor inequalities in an acute trust: a retrospective study

<p><b>Abstract</b></p> <p><b>Background</b></p> <p>Reducing inequalities is one of the priorities of the National Health Service. However, there is no standard system for monitoring inequalities in the care provided by acute trusts. We explore the feasibility of monitoring inequalities within an acute trust using routine data.</p> <p><b>Methods</b></p> <p>A retrospective study of hospital episode statistics from one acute trust in London over three years (2007 to 2010). Waiting times, length of stay and readmission rates were described for seven common surgical procedures. Inequalities by age, sex, ethnicity and social deprivation were examined using multiple logistic regression, adjusting for the other socio-demographic variables and comorbidities. Sample size calculations were computed to estimate how many years of data would be ideal for this analysis.</p> <p><b>Results</b></p> <p>This study found that even in a large acute trust, there was not enough power to detect differences between subgroups. There was little evidence of inequalities for the outcome and process measures examined, statistically significant differences by age, sex, ethnicity or deprivation were only found in 11 out of 80 analyses. Bariatric surgery patients who were black African or Caribbean were more likely than white patients to experience a prolonged wait (longer than 64 days, aOR = 2.47, 95% CI: 1.36-4.49). Following a coronary angioplasty, patients from more deprived areas were more likely to have had a prolonged length of stay (aOR = 1.66, 95% CI: 1.25-2.20).</p> <p><b>Conclusions</b></p> <p>This study found difficulties in using routine data to identify inequalities on a trust level. Little evidence of inequalities in waiting time, length of stay or readmission rates by sex, ethnicity or social deprivation were identified although some differences were identified which warrant further investigation. Even with three years of data from a large trust there was little power to detect inequalities by procedure. Data will therefore need to be pooled from multiple trusts to detect inequalities.</p

Using routinely recorded ethnicity: analysis of waiting times for elective admissions by ethnic group.

OBJECTIVE: To assess whether patients from non-white ethnic groups wait longer than white patients for elective in-patient admissions at St Mary's Hospital in London. METHODS: Patients who came off the waiting list for an elective inpatient admission between 1 April 2000 and 31 March 2001 were selected. A multivariable log linear model was developed to assess geometric mean waiting times for Black, Asian, Other and Missing ethnic groups compared to the White group, adjusted for age, sex, urgency and distance. RESULTS: Caution is needed in interpreting results, as a large number of patients had no usable ethnic code. There was no strong evidence that waiting times for ethnic groups were systematically different than for the White group. However, there was some evidence that white patients waited longer for a coronary arteriography than patients in other ethnic groups. This was partially explained by age, sex, clinical urgency and residential distance from St Mary's. CONCLUSIONS: The large proportion of patients with no usable ethnic code, lack of robust methods for case-mix adjustment and multiple ethnic categories makes analysis methodologically difficult. Regular and informative analysis of ethnic coded data is a necessary step in improving the accuracy and completeness of coding