scholarly journals Changes in soft drinks purchased by British households associated with the UK soft drinks industry levy: controlled interrupted time series analysis

BMJ ◽  
2021 ◽  
pp. n254 ◽  
Author(s):  
David Pell ◽  
Oliver Mytton ◽  
Tarra L Penney ◽  
Adam Briggs ◽  
Steven Cummins ◽  
...  
Keyword(s):  
Time Series ◽  
Confidence Interval ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
Soft Drinks ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Market Research Company ◽  
One Year ◽  
The Uk

Abstract Objective To determine changes in household purchases of drinks and confectionery one year after implementation of the UK soft drinks industry levy (SDIL). Design Controlled interrupted time series analysis. Participants Members of a panel of households reporting their purchasing on a weekly basis to a market research company (average weekly number of participants n=22 183), March 2014 to March 2019. Intervention A two tiered tax levied on manufacturers of soft drinks, announced in March 2016 and implemented in April 2018. Drinks with ≥8 g sugar/100 mL (high tier) are taxed at £0.24/L and drinks with ≥5 to <8 g sugar/100 mL (low tier) are taxed at £0.18/L. Drinks with <5 g sugar/100 mL (no levy) are not taxed. Main outcome measures Absolute and relative differences in the volume of, and amount of sugar in, soft drinks categories, all soft drinks combined, alcohol, and confectionery purchased per household per week one year after implementation of the SDIL compared with trends before the announcement of the SDIL. Results In March 2019, compared with the counterfactual estimated from pre-announcement trends, purchased volume of drinks in the high levy tier decreased by 155 mL (95% confidence interval 240.5 to 69.5 mL) per household per week, equivalent to 44.3% (95% confidence interval 59.9% to 28.7%), and sugar purchased in these drinks decreased by 18.0 g (95% confidence interval 32.3 to 3.6 g), or 45.9% (68.8% to 22.9%). Purchases of low tier drinks decreased by 177.3 mL (225.3 to 129.3 mL) per household per week, or 85.9% (95.1% to 76.7%), with a 12.5 g (15.4 to 9.5 g) reduction in sugar in these drinks, equivalent to 86.2% (94.2% to 78.1%). Despite no overall change in volume of no levy drinks purchased, there was an increase in sugar purchased of 15.3 g (12.6 to 17.9 g) per household per week, equivalent to 166.4% (94.2% to 238.5%). When all soft drinks were combined, the volume of drinks purchased did not change, but sugar decreased by 29.5 g (55.8 to 3.1 g), or 9.8% (17.9% to 1.8%). Purchases of confectionery and alcoholic drinks did not change. Conclusions Compared with trends before the SDIL was announced, one year after implementation, the volume of soft drinks purchased did not change. The amount of sugar in those drinks was 30 g, or 10%, lower per household per week—equivalent to one 250 mL serving of a low tier drink per person per week. The SDIL might benefit public health without harming industry. Trial registration ISRCTN18042742.

scholarly journals Beyond reasonable drought: hotspots reveal a link between the ‘Big Dry’ and cryptosporidiosis in Australia's Murray Darling Basin

2018 ◽  
Vol 16 (6) ◽  
pp. 1033-1037 ◽  
Author(s):  
Aparna Lal ◽  
Paul Konings
Keyword(s):  
Time Series ◽  
Confidence Interval ◽  
Time Series Analysis ◽  
Drainage Basin ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
The North ◽  
Spatio Temporal ◽  
The Impact

Abstract There is little evidence on how the health impacts of drought vary spatially and temporally. With a focus on waterborne cryptosporidiosis, we identify spatio-temporal hotspots and by using interrupted time series analysis, examine the impact of Australia's Big Dry (2001–2009) in these disease clusters in the Murray Darling Drainage Basin. Analyses revealed a statistically significant hotspot in the north of the Australian Capital Territory (ACT) and a hotspot in the north-eastern end of the basin in Queensland. After controlling for long-term trend and seasonality in cryptosporidiosis, interrupted time series analysis of reported cases in these hotspots indicated a statistically significant link with the Big Dry. In both areas, the end of the Big Dry was associated with a lower risk of reported cryptosporidiosis; in the ACT, the estimated relative risk (RR) was 0.16 (95% confidence interval: 0.07; 0.33), and in Queensland the RR was 0.42 (95% confidence interval: 0.19; 0.42). Although these data do not establish a causal association, this research highlights the potential for drought-related health risks.

scholarly journals Decreasing Boarders in the Emergency Department By Reducing Clerical Work in the Discharge Process of In-Hospital Patients – An Interrupted Time-Series Analysis

2021 ◽  
Author(s):  
Diego Marques Moroço ◽  
Antonio Pazin-Filho
Keyword(s):  
Time Series ◽  
Confidence Interval ◽  
Time Series Analysis ◽  
Digital Signature ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Post Intervention ◽  
Clerical Work ◽  
Series Analysis ◽  
Hospital Patients

Abstract Background: Emergency Department (ED) boarding is related to in-hospital patients' discharge. New techniques implemented in hospital institutions, such as digital signature, offer an improvement on these processes.Goals: Evaluate the impact of expediting patient's discharge after medical orders with the number of patients diverted to ED.Methods: We conducted a quasi-experimental study before and after an intervention. It consisted of an encrypted digital signature used to reduce clerical work and expedite the patient's release from the institution after medical discharge. We used Interrupted Time Series Analysis based on administrative data (number of hospital discharge, bed turnover, the time between medical discharge and the appointment's closing) from 2011 to 2019 using.Results: The interrupted time series analysis for the time from medical order to virtually hospital discharge showed an immediate change in level (Coefficient β2 -3.6 hours - 95% confidence interval -3.9; -3.4 - Lag1), but not a difference in the slope of the behavior of the post-intervention curve (β3 0.0005 coefficient - 95% confidence interval -0.0040; 0.0050 - Lag1). For the number of diverged patients to ED, we observed no immediate change in level (Coefficient β2 -0.84 patients - 95% confidence interval -0.33; 0.16 - Lag1), but a difference in the slope of the behavior of the post-intervention curve (β3 0.0005 coefficient - 95% confidence interval -0.0040; 0.0050 - Lag1).Conclusion: Reducing clerical work and so expediting patient discharge was associated with a decrease of potential boarders to ED.

scholarly journals Does admission prevalence change after reconfiguration of inpatient services? An interrupted time series analysis of the impact of reconfiguration in five centres

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Joanne Martin ◽  
Edwin Amalraj Raja ◽  
Steve Turner
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Emergency Admission ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Emergency Admissions ◽  
Series Analysis ◽  
Inpatient Services ◽  
The Impact ◽  
Admission Prevalence

Abstract Background Service reconfiguration of inpatient services in a hospital includes complete and partial closure of all emergency inpatient facilities. The “natural experiment” of service reconfiguration may give insight into drivers for emergency admissions to hospital. This study addressed the question does the prevalence of emergency admission to hospital for children change after reconfiguration of inpatient services? Methods There were five service reconfigurations in Scottish hospitals between 2004 and 2018 where emergency admissions to one “reconfigured” hospital were halted (permanently or temporarily) and directed to a second “adjacent” hospital. The number of emergency admissions (standardised to /1000 children in the regional population) per month to the “reconfigured” and “adjacent” hospitals was obtained for five years prior to reconfiguration and up to five years afterwards. An interrupted time series analysis considered the association between reconfiguration and admissions across pairs comprised of “reconfigured” and “adjacent” hospitals, with adjustment for seasonality and an overall rising trend in admissions. Results Of the five episodes of reconfiguration, two were immediate closure, two involved closure only to overnight admissions and one with overnight closure for a period and then closure. In “reconfigured” hospitals there was an average fall of 117 admissions/month [95% CI 78, 156] in the year after reconfiguration compared to the year before, and in “adjacent” hospitals admissions rose by 82/month [32, 131]. Across paired reconfigured and adjacent hospitals, in the months post reconfiguration, the overall number of admissions to one hospital pair slowed, in another pair admissions accelerated, and admission prevalence was unchanged in three pairs. After reconfiguration in one hospital, there was a rise in admissions to a third hospital which was closer than the named “adjacent” hospital. Conclusions There are diverse outcomes for the number of emergency admissions post reconfiguration of inpatient facilities. Factors including resources placed in the community after local reconfiguration, distance to the “adjacent” hospital and local deprivation may be important drivers for admission pathways after reconfiguration. Policy makers considering reconfiguration might consider a number of factors which may be important determinants of admissions post reconfiguration.

Recession and risk of suicide in Denmark during the 2009 global financial crisis: an ecological register-based study

2021 ◽  
pp. 140349482110132
Author(s):  
Agnieszka Konieczna ◽  
Sarah Grube Jakobsen ◽  
Christina Petrea Larsen ◽  
Erik Christiansen
Keyword(s):  
Time Series ◽  
Financial Crisis ◽  
Time Series Analysis ◽  
Suicide Rate ◽  
Global Financial Crisis ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Prevention Programmes ◽  
The Impact

Aim: The aim of this study is to analyse the potential impact from the financial crisis (onset in 2009) on suicide rates in Denmark. The hypothesis is that the global financial crisis raised unemployment which leads to raising the suicide rate in Denmark and that the impact is most prominent in men. Method: This study used an ecological study design, including register data from 2001 until 2016 on unemployment, suicide, gender and calendar time which was analysed using Poisson regression models and interrupted time series analysis. Results: The correlation between unemployment and suicide rates was positive in the period and statistically significant for all, but at a moderate level. A dichotomised version of time (calendar year) showed a significant reduction in the suicide rate for women (incidence rate ratio 0.87, P=0.002). Interrupted time series analysis showed a significant decreasing trend for the overall suicide rate and for men in the pre-recession period, which in both cases stagnated after the onset of recession in 2009. The difference between the genders’ suicide rate changed significantly at the onset of recession, as the rate for men increased and the rate for women decreased. Discussion: The Danish social welfare model might have prevented social disintegration and suicide among unemployed, and suicide prevention programmes might have prevented deaths among unemployed and mentally ill individuals. Conclusions: We found some indications for gender-specific differences from the impact of the financial crises on the suicide rate. We recommend that men should be specifically targeted for appropriate prevention programmes during periods of economic downturn.

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