Increase in premature mortality due to non-communicable diseases in Sri Lanka during the first decade of the twenty-first century

Ediriweera, Dileepa Senajith; Karunapema, Palitha; Pathmeswaran, A.; Arnold, Mahendra

doi:10.1186/s12889-018-5503-9

Cited by 21 publications

(17 citation statements)

References 4 publications

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“…It has been described that as age increases one becomes more exposed to the risk factors for long periods until the complications develop and hence experiences the clinical syndromes of NCDs [46]. Like in our study, males accounted for most NCD deaths in studies in Brazil, Sri Lanka, and China [47][48][49]. Despite the observations that NCD deaths affected more males than females, several studies in Tanzania have reported that women have a higher risk of being obese than men, hence more vulnerable to several NCDs [50][51][52].…”

Section: Discussionsupporting

confidence: 69%

Patterns and trends of hospital mortality due to non-communicable diseases and injuries in Tanzania: a 10- year retrospective analysis

Mboera¹,

Kishamawe²,

Rumisha³

et al. 2020

Preprint

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Background: Globally, non-communicable diseases (NCD) kill about 40 million people annually, with about three-quarters of the deaths occurring in low and middle-income countries. This study was carried out to determine the patterns, trends, and causes of non-communicable disease mortality in hospitals of Tanzania from 2006-2015.Methods: This retrospective study involved primary, secondary, tertiary, and specialized hospitals in Tanzania. Death statistics were extracted from inpatient department registers, death registers, and International Classification of Diseases (ICD) report forms. Variables collected were deceased’s age, sex, cause and date of death. The ICD-10 coding system was used to assign each death to its underlying cause. Data were analysed using STATA version 14. Results: A total of 247,976 deaths were reported during the 10 years (2006–2015) in 39 hospitals. Of the total deaths, 67,711 (27.3%) were due to non-communicable diseases (NCD) and injuries. Cardio-circulatory diseases (31.9%), cancers (18.6%), chronic respiratory diseases (18.4%), and injuries (17.9%) accounted for the largest proportion (86.8%) of deaths due to NCDs. The majority (57.6%) of deaths due to NCD occurred among males. Overall, the total deaths from NCDs increased by 153.3% from 4,298 in 2006 to 10,886 in 2015. The age group 15-59 years (53.4%) was the most affected category. The overall 10-year annual age-standardized mortality rate (ASMR) for all NCDs and injuries was 235.2 per 100,0000 population. It was higher for males (287.2/100,000) than for females (186.7/100,000). The annual ASMR increased from 11.9 in 2006 to 36.5 per 100,000 populations in 2015. Most of the NCD deaths occurred in the secondary (40.0%) and primary level hospitals (27.8%). There were variations in the type of non-communicable diseases by geographical distributions. Conclusions: There was a substantial increase in ASMR due to NCDs and injuries in Tanzania from 2006 to 2015. Most of the deaths due to NCD and injuries affected the productive young adult group and males. The burden caused by NCD in the most productive ages means that families, communities, and the nation at large suffer from premature deaths. The government of Tanzania must invest in early detection and timely treatment of NCDs to reduce premature deaths.

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Section: Discussionsupporting

confidence: 69%

Patterns and trends of hospital mortality due to non-communicable diseases and injuries in Tanzania: a 10- year retrospective analysis

Mboera¹,

Kishamawe²,

Rumisha³

et al. 2020

Preprint

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“…The high average number of medicines per prescription indicates a high degree of polypharmacy, generally considered when 4 or more medicines are prescribed per prescription. This could be due to recent changes in the epidemiological trend of diseases, with an increasing prevalence of noncommunicable diseases such as diabetes, hypertension, and coronary artery disease [ 20 ]. Furthermore, these diseases are often coexistent, which necessitates the simultaneous prescription of multiple medications for the same patient.…”

Section: Discussionmentioning

confidence: 99%

Core Prescribing Indicators and the Most Commonly Prescribed Medicines in a Tertiary Health Care Setting in a Developing Country

Galappatthy

Ranasinghe

Liyanage

et al. 2021

Advances in Pharmacological and Pharmaceutical Sciences

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Irrational prescribing is common, especially in developing countries. It is important to identify the magnitude of irrational use, to take necessary steps to promote rational prescribing. We identified core prescribing indicators and commonly prescribed medicines at ward settings (IW) and outpatients’ clinics (OPC) in a tertiary care hospital in Sri Lanka. A descriptive cross-sectional study was carried out at IW and OPC settings. Prescriptions were obtained from 5 major specialties (Clinical Medicine (CM), Gynaecology and Obstetrics (GO), Paediatrics, Psychiatry, and Surgery). The WHO core prescribing indicators were used to describe the pattern of prescribing, and the most commonly prescribed medicines were identified. A total of 1,318 prescriptions were analyzed. The five most commonly prescribed medicines were paracetamol (31.0%), omeprazole (20.6%), folic acid (18.3%), atorvastatin (16.2%), and salbutamol (15.3%). The average number of medicines per encounter was 4.8 ± 3.6 (IW: 5.7 ± 4; OPC: 3.8 ± 2.8; p < 0.001 ), with the highest IW (7.8 ± 4.2) and OPC (7.8 ± 2.7) values were from CM, being significantly higher than all other disciplines ( p < 0.05 ). Percentage encounters with an antibiotic or an injection was 26.4% and 30.1%, respectively, with IW being significantly higher than OPC ( p < 0.001 ). Percentage of medicines prescribed by generic name and from the essential medicine list (EML) was 90.1% and 91.1%, respectively, with no significant IW and OPC difference. In conclusion, a high degree of polypharmacy was noted. The use of injectable medicines, prescribing from the EML, and generic name prescribing was satisfactory; however, overall rational prescribing needs further improvement. Further investigation into the degree of rational prescribing associating it with clinical information will be important.

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“…A key component of population health status is premature mortality, defined as a death occurring before the age of 75 years [1,2]. Premature mortality is a major public health problem both in the United States and worldwide, and it is exacerbated by socioeconomic disparities [3][4][5]. Stretching along the Appalachian Mountains and covering the area over 200,000 square miles, the Appalachian Region is composed of 420 counties across 13 states -parts of Alabama, Georgia, Kentucky, Maryland, Mississippi, New York, North Carolina, Ohio, Pennsylvania, South Carolina, Tennessee, and Virginia, and the entire state of West Virginiaand has a population of 25 million people [6].…”

Section: Introductionmentioning

confidence: 99%

Community Characteristics Associated with Premature Mortality in the Appalachian Region

Сергеев

2021

BJSTR

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Background: A key component of population health status is premature mortality, defined as a death occurring before the age of 75 years. Of particular concern is premature mortality among vulnerable populations of Appalachia. However, it remains unclear what specific community characteristics are the leading predictors of premature mortality in the Appalachian population to be considered when developing high-priority interventions to improve premature mortality.Objective: We hypothesized that a limited number of community characteristics would account for most of premature deaths in the Appalachian population. The objective of our study was to identify these essential community characteristics.Methods: County Health Rankings and Roadmaps data were used to investigate premature mortality, as measured by the number of years of potential life lost (YPLL) before age 75 years per 100,000 population (age-adjusted), and associated community characteristics in the 13 Appalachian states. Counties' rurality status was defined using the United States Departments of Agriculture Economic Research Service's (USDA ERS) Rural-Urban Continuum Codes (RUCC). Descriptive and inferential statistical analyses, including multiple regression, were conducted using SAS and SPSS. A conventional Type I error (alpha) level of 0.05 (p<0.05) was used for all analyses.Results: Premature mortality rates, as measured by the number of years of potential life lost (YPLL) before age 75 years, in the 420 Appalachian counties were statistically significantly higher than in their counterparts -the 679 non-Appalachian counties of the 13 Appalachian states: 9,299.7 vs. 8,425.4 per 100,000 (p<0.001). Within the Appalachian counties, premature mortality rates were statistically significantly higher in rural areas than in urban areas: YPLL 10,010.9 vs. 8,546.6 per 100,000 (p<0.001). Multivariable analysis identified key factors predicting premature mortality in the Appalachian population that can be grouped into three major categories: health behavior, health care, and social environment factors.Conclusions: Premature mortality in rural Appalachian counties is statistically significantly higher than in urban Appalachian counties. The key predictors of premature mortality in the Appalachian Region can be grouped into three major categories: health behavior; health care; and social environment factors. This study furthers the body of knowledge necessary to develop targeted interventions to improve premature mortality in the Appalachian Region.

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Increase in premature mortality due to non-communicable diseases in Sri Lanka during the first decade of the twenty-first century

Cited by 21 publications

References 4 publications

Patterns and trends of hospital mortality due to non-communicable diseases and injuries in Tanzania: a 10- year retrospective analysis

Patterns and trends of hospital mortality due to non-communicable diseases and injuries in Tanzania: a 10- year retrospective analysis

Core Prescribing Indicators and the Most Commonly Prescribed Medicines in a Tertiary Health Care Setting in a Developing Country

Community Characteristics Associated with Premature Mortality in the Appalachian Region

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