scholarly journals Studying trajectories of multimorbidity: a systematic scoping review of longitudinal approaches and evidence

BMJ Open ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. e048485
Author(s):  
Genevieve Cezard ◽  
Calum Thomas McHale ◽  
Frank Sullivan ◽  
Juliana Kuster Filipe Bowles ◽  
Katherine Keenan
Keyword(s):  
Low Income ◽  
Latent Class ◽  
Health Behaviours ◽  
Research Area ◽  
Multilevel Regression ◽  
Cross Sectional ◽  
Middle Income ◽  
Diverse Range ◽  
Online Databases ◽  
Growth Curve Modelling

ObjectivesMultimorbidity—the co-occurrence of at least two chronic diseases in an individual—is an important public health challenge in ageing societies. The vast majority of multimorbidity research takes a cross-sectional approach, but longitudinal approaches to understanding multimorbidity are an emerging research area, being encouraged by multiple funders. To support development in this research area, the aim of this study is to scope the methodological approaches and substantive findings of studies that have investigated longitudinal multimorbidity trajectories.DesignWe conducted a systematic search for relevant studies in four online databases (Medline, Scopus, Web of Science and Embase) in May 2020 using predefined search terms and inclusion and exclusion criteria. The search was complemented by searching reference lists of relevant papers. From the selected studies, we systematically extracted data on study methodology and findings and summarised them in a narrative synthesis.ResultsWe identified 35 studies investigating multimorbidity longitudinally, all published in the last decade, and predominantly in high-income countries from the Global North. Longitudinal approaches employed included constructing change variables, multilevel regression analysis (eg, growth curve modelling), longitudinal group-based methodologies (eg, latent class modelling), analysing disease transitions and visualisation techniques. Commonly identified risk factors for multimorbidity onset and progression were older age, higher socioeconomic and area-level deprivation, overweight and poorer health behaviours.ConclusionThe nascent research area employs a diverse range of longitudinal approaches that characterise accumulation and disease combinations and to a lesser extent disease sequencing and progression. Gaps include understanding the long-term, life course determinants of different multimorbidity trajectories, and doing so across diverse populations, including those from low-income and middle-income countries. This can provide a detailed picture of morbidity development, with important implications from a clinical and intervention perspective.

scholarly journals Studying trajectories of multimorbidity: a systematic scoping review of longitudinal approaches and evidence

2020 ◽  
Author(s):  
Genevieve Cezard ◽  
Calum McHale ◽  
Frank Sullivan ◽  
Juliana Bowles ◽  
Katherine Keenan
Keyword(s):  
Scoping Review ◽  
Latent Class ◽  
Health Behaviours ◽  
Research Area ◽  
Multilevel Regression ◽  
Cross Sectional ◽  
Middle Income ◽  
Diverse Range ◽  
Growth Curve Modelling ◽  
The Life Course

AbstractIntroductionMultimorbidity is an important public health challenge in ageing societies. While most multimorbidity research takes a cross-sectional approach, longitudinal approaches to understanding multimorbidity are an emerging research area. We aim to scope the methodological approaches and substantive findings of studies analysing multimorbidity trajectories.MethodsWe identified studies employing longitudinal methodologies to explore multimorbidity trajectories using a scoping review approach. A systematically search for relevant studies was carried via four academic databases (Medline, Scopus, Web of Science, and Embase) complemented by professional networks and reference lists.ResultsOur review identified 34 studies investigating multimorbidity longitudinally, all published in the last decade, and with a clear lack of research based on low- and middle-income country data. Longitudinal approaches included constructing variables of change, multilevel regression analysis (e.g. growth curve modelling), longitudinal group-based methodologies (e.g. latent class modelling), analysing disease transitions, and visualisation techniques. Commonly identified risk factors for multimorbidity onset and progression were older age, higher deprivation, overweight, and poorer health behaviours.ConclusionThe nascent research area employs a diverse range of longitudinal approaches that characterize accumulation and disease combinations, and to a lesser extent disease sequencing and progression. Understanding the life course determinants of different multimorbidity trajectories across diverse populations and settings can provide a detailed picture of morbidity development, with important implications from a clinical and intervention perspective.

Inpatients’ experience and the associated factors: A cross-sectional study at Lung hospital, Son La, in 2020

2021 ◽  
Vol 05 (04) ◽  
pp. 110-116
Author(s):  
Huu Thang Nguyen ◽  
◽  
Thi Nguyet Minh Doan ◽  
Thanh Huong Tran ◽  
Hai Thanh Pham
Keyword(s):  
Low Income ◽  
Associated Factors ◽  
Income Group ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Related Factors ◽  
Cross Sectional ◽  
Middle Income ◽  
Medical Facilities ◽  
Middle Income Group

Objectives: Medical facilities with an autonomous tendency always try to serve positive and pleasant experiences to improve the brand name, increase patient satisfaction and loyalty. A descriptive cross-sectional study was conducted on 245 inpatients at Lung Hospital in Son La province in 2020. To describe the current situation of the inpatient's experience at Lung Hospital in Son La province by 2020 and its related factors. Methods: This was a cross-sectional study conducted on 245 inpatients at Son La Lung Hospital Results: The study showed that the total score of inpatients’ experience ranged from 22 points to 57 points and the mean of it was 39.7 (6.13) points. Subject's experience scores were divided into 2 groups, the satisfied group accounted for 32.7% and the percentage of the unsatisfied group was 67.3%. As compared to men, a higher total score of women was (OR: 1.134; 95% CI: 0.284-0.997). The urban area group’s score was 1,190 times higher than that of those who live in rural and mountainous areas (95% CI: 1,010 - 1,400). The middle-income group had more positive experience than the low-income group (OR: 1.180; 95% CI: 1.010 - 1.370). Conclusions: Our research showed that gender, living area and economic condition affected the total score of inpatients’ experience at the Lung hospital. Keywords: Patient experiences, inpatient treatment, hospital, associated factors

scholarly journals Efficacy of deep learning methods for predicting under-five mortality in 34 low-income and middle-income countries

BMJ Open ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. e034524
Author(s):  
Adeyinka Emmanuel Adegbosin ◽  
Bela Stantic ◽  
Jing Sun
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Low Income ◽  
Maternal Education ◽  
Household Wealth ◽  
Secondary Outcome ◽  
Cross Sectional ◽  
Middle Income ◽  
Under Five ◽  
Middle Income Countries

ObjectivesTo explore the efficacy of machine learning (ML) techniques in predicting under-five mortality (U5M) in low-income and middle-income countries (LMICs) and to identify significant predictors of U5M.DesignThis is a cross-sectional, proof-of-concept study.Settings and participantsWe analysed data from the Demographic and Health Survey. The data were drawn from 34 LMICs, comprising a total of n=1 520 018 children drawn from 956 995 unique households.Primary and secondary outcome measuresThe primary outcome measure was U5M; secondary outcome was comparing the efficacy of deep learning algorithms: deep neural network (DNN); convolution neural network (CNN); hybrid CNN-DNN with logistic regression (LR) for the prediction of child’s survival.ResultsWe found that duration of breast feeding, number of antenatal visits, household wealth index, postnatal care and the level of maternal education are some of the most important predictors of U5M. We found that deep learning techniques are superior to LR for the classification of child survival: LR sensitivity=0.47, specificity=0.53; DNN sensitivity=0.69, specificity=0.83; CNN sensitivity=0.68, specificity=0.83; CNN-DNN sensitivity=0.71, specificity=0.83.ConclusionOur findings provide an understanding of determinants of U5M in LMICs. It also demonstrates that deep learning models are more efficacious than traditional analytical approach.

scholarly journals Reporting of inequalities in blindness in low income and middle income countries: a review of cross sectional surveys

2017 ◽  
Vol 46 (1) ◽  
pp. 99-100 ◽  
Author(s):  
Jacqueline Ramke ◽  
Anna Palagyi ◽  
Jennifer Petkovic ◽  
Clare E Gilbert
Keyword(s):  
Low Income ◽  
Cross Sectional ◽  
Middle Income ◽  
Middle Income Countries

Are low-to-middle-income households experiencing food insecurity in Victoria, Australia? An examination of the Victorian Population Health Survey, 2006–2009

2017 ◽  
Vol 23 (3) ◽  
pp. 249 ◽  
Author(s):  
Sue Kleve ◽  
Zoe E. Davidson ◽  
Emma Gearon ◽  
Sue Booth ◽  
Claire Palermo
Keyword(s):  
Food Insecurity ◽  
Population Health ◽  
Low Income ◽  
Home Ownership ◽  
Cross Sectional ◽  
Middle Income ◽  
Income Levels ◽  
Factors Associated ◽  
Health And Wellbeing ◽  
Using Data

Food insecurity affects health and wellbeing. Little is known about the relationship between food insecurity across income levels. This study aims to investigate the prevalence and frequency of food insecurity in low-to-middle-income Victorian households over time and identify factors associated with food insecurity in these households. Prevalence and frequency of food insecurity was analysed across household income levels using data from the cross-sectional 2006–09 Victorian Population Health Surveys (VPHS). Respondents were categorised as food insecure, if in the last 12 months they had run out of food and were unable to afford to buy more. Multivariable logistic regression was used to describe factors associated with food insecurity in low-to-middle-income households (A$40000–$80000 in 2008). Between 4.9 and 5.5% for total survey populations and 3.9–4.8% in low-to-middle-income respondents were food insecure. Food insecurity was associated with limited help from friends, home ownership status, inability to raise money in an emergency and cost of some foods. Food insecurity exists in households beyond those on a very low income. Understanding the extent and implications of household food insecurity across all income groups in Australia will inform effective and appropriate public health responses.

scholarly journals The ISN 0by25 Global Snapshot Study

2016 ◽  
Vol 68 (Suppl. 2) ◽  
pp. 29-31 ◽  
Author(s):  
John Feehally
Keyword(s):  
Low Income ◽  
Kidney Injury ◽  
Complete Recovery ◽  
Cross Sectional Study ◽  
Low Income Countries ◽  
Clinical Indication ◽  
Partial Recovery ◽  
Cross Sectional ◽  
Middle Income ◽  
New Information

The International Society of Nephrology's (ISN) 0by25 initiative aims to prevent avoidable deaths from acute kidney injury (AKI) by 2025, most of which occur in low and lower middle-income countries (LLMICs). To increase evidence about the epidemiology of AKI, especially in LLMICs, ISN conducted a ‘Global Snapshot', a multinational, cross-sectional study in which 322 physicians from 72 countries in 6 continents identified 3,664 adults and 354 children with AKI who were under their care of which 45% were from LLMICs, nevertheless low-income countries were under-represented. In LLMICs, patients with AKI were younger, and community acquired AKI was more common. Hypotension (40%) and dehydration (39%) were the most common causes of AKI. Dehydration was a more common cause in LLMIC, as were sepsis, pregnancy-related AKI and animal envenomation. Acute dialysis was performed in 23% of patients. Eight percent had a clinical indication for this but were not dialyzed. In LLMICs, lack of resources (16%) and inability to afford therapy (30%) accounted for almost half of these cases. Overall mortality at 7 days was 11% and was higher in LLMICs. Complete recovery from AKI occurred in 30% of patients and partial recovery 37%, and was more often complete in LLMICs. The 0by25 Global Snapshot provides new information about the worldwide epidemiology of AKI, helping to identify elements that would be amenable in intervention to reduce preventable deaths.

scholarly journals Prevalence of substance use in Bangladesh

2020 ◽  
Vol 32 (1) ◽  
pp. 1-8
Author(s):  
Md Faruq Alam ◽  
Mekhala Sarkar ◽  
Mohammad Tariqul Alam ◽  
Helal Uddin Ahmed ◽  
Avra Das Bhowmik ◽  
...  
Keyword(s):  
Mental Health ◽  
Substance Use ◽  
Low Income ◽  
Sampling Technique ◽  
Income Group ◽  
Cross Sectional Study ◽  
Cluster Sampling ◽  
Statistical Parameters ◽  
Cross Sectional ◽  
Middle Income

The prevalence of substance use is on rising trend in the country. This two-stage nationwide multicentric community based cross sectional study was conducted by National Institute of Mental Health (NIMH), Dhaka during the period of September 2017 to July 2018 to determine the prevalence of substance use as well as to identify the proportion of users used different substances and to find out socio-demographic correlates of substance use in Bangladesh. The sample were collected by cluster sampling technique. In the first stage data were collected from 19692 respondents aged between 7 years and above in 140 clusters through face-to-face interview using semi-structured questionnaires to collect information by trained data collector. Diagnoses of substance use were made in the second stage of interview by research psychiatrists following DSM-5 diagnostic criteria of mental disorders. Descriptive and inferential statistics of the collected data was done using standard statistical parameters. SPSS programme (Version 23) was used to summarize and to analyze the data. The results showed that, the prevalence of substance use was found as 3.3% among the population 18 years and above. Prevalence of substance use was 4.8% in male and 0.6% in female. Most frequently used substances include cannabis in (42.7%), alcohol in 27.5%, amphetamine (yaba) in 15.2%, opioid in 5.3% and sleeping pills in 3.4% users. Among professions of substance users 6.7% were labors, 5.7% unemployed, 4.3% business men, 3.8% farmers and 3.5% service holders. Extremes of social classes were found as increased users of substances such as people with low income 3.2% and people with high income 3.8% using as against 2.6% in middle income group. The data of this community survey will be used for planning of mental health services in Bangladesh. Bang J Psychiatry June 2018; 32(1): 1-8

scholarly journals Socioeconomic Disparities in Drugs and Substance Abuse: results from a Household Cross-sectional Survey in Murang’ a County, Kenya

2020 ◽  
Author(s):  
Vincent Omondi Were ◽  
Collins Omondi Okoyo ◽  
Sylvie Biyaki Araka ◽  
Henry Muriuki Kanyi ◽  
Elizabeth Echoka Echoka ◽  
...  
Keyword(s):  
Substance Abuse ◽  
Prescription Drugs ◽  
Low Income ◽  
Economic Burden ◽  
Multivariate Logistic Regression Analysis ◽  
Cross Sectional ◽  
Middle Income ◽  
Household Level ◽  
Income Groups ◽  
Economic Inequalities

Abstract IntroductionDrugs and substance abuse has adverse health effects and substantial economic burden to the global economies and at the household level. There is, however, limited data on socio-economic inequalities disparities in drugs and substance abuse in low-to-middle income countries such as Kenya. This study aimed to assess the socio-economic inequalities in a selected county of central Kenya.MethodThe study design was cross-sectional, and data collection was conducted between November and December 2017. A total of 449 households with a least one person who uses any drugs or substance of abuse were randomly sampled from 4 purposively selected sub-locations of Murang’ a County, central Kenya. Structured questionnaires were used to collect data on types of drugs used, economic burden, and gender roles at the household level. Household socio-economic status (SES) was established ( low, middle, and high SES ) using principal component analysis f(PCA) from a set of household assets and characteristics. Multivariate logistic regression analysis was used to assess the association between SES, gender, and other factors on the uptake of drugs and substance of abuse.ResultsIndividuals in higher SES were more likely to use cigarettes ( OR = 2.13; 95%CI = 1.25–3.61, p = 0.005) or piped tobacco (OR = 11.37; 95% CI, 2.55–50.8; p-value = 0.001) than those in low SES. The wealthier individuals were less likely to use legal alcohol (OR = 0.39; 95%CI = 0.21–0.71, p = 0.002) than the poorest individuals. The use of prescription drugs did not vary with SES. A comparison of the median amount of money spent on acquiring drugs showed that richer individuals spent a significantly higher amount than the poorest individuals (Ksh 1500 vs. Ksh 1000, p = 0.0310). Deaths related to drugs and substance abuse were more likely to occur in middle SES than amongst the poorest households (OR = 2.96; 95%CI = 1.03–8.45).ConclusionSocioeconomic disparities exist in the use of drugs and substance abuse. The low-income individuals are at a higher risk of abuse and thus of economic burden due to catastrophic expenditure in acquiring the drugs. Cases of deaths were likely to occur in middle-income groups. Strategies to reduce drugs and substance abuse must address socio-economic inequalities through targeted approaches to individuals in low-income groups.

scholarly journals The COVID-19 vaccination experience in Bangladesh: Findings from a cross-sectional study

2021 ◽  
Vol 35 ◽  
pp. 205873842110656
Author(s):  
Md. Rabiul Islam ◽  
Moynul Hasan ◽  
Waheeda Nasreen ◽  
Md. Ismail Tushar ◽  
Mohiuddin Ahmed Bhuiyan
Keyword(s):  
Adverse Events ◽  
Low Income ◽  
Heart Diseases ◽  
Developed Countries ◽  
Cross Sectional Study ◽  
Low Income Countries ◽  
Sectional Study ◽  
Cross Sectional ◽  
Middle Income ◽  
Mass Immunization

Objectives Vaccination rollout against COVID-19 has started in developed countries in early December 2020. Mass immunization for poor or low-income countries is quite challenging before 2023. Being a lower–middle-income country, Bangladesh has begun a nationwide COVID-19 vaccination drive in early February 2021. Here, we aimed to assess the opinions, experiences, and adverse events of the COVID-19 vaccination in Bangladesh. Methods We conducted this online cross-sectional study from 10 February 2021, to 10 March 2021, in Bangladesh. A self-reported semi-structured survey questionnaire was used using Google forms. We recorded demographics, disease history, medication records, opinions and experiences of vaccination, and associated adverse events symptoms. Results We observed leading comorbid diseases were hypertension (25.9%), diabetes (21.1%), heart diseases (9.3%), and asthma (8.7%). The most frequently reported adverse events were injection site pain (34.3%), fever (32.6%), headache (20.2%), fatigue (16.6%), and cold feeling (15.4%). The chances of having adverse events were significantly higher in males than females ( p = 0.039). However, 36.4% of respondents reported no adverse events. Adverse events usually appeared after 12 h and went way within 48 h of vaccination. Besides, 85.5% were happy with the overall vaccination management, while 88.0% of the respondents recommended the COVID-19 vaccine for others for early immunization. Conclusion According to the present findings, reported adverse events after the doses of Covishield in Bangladesh were non-serious and temporary. In Bangladesh, the early vaccination against COVID-19 was possible due to its prudent vaccine deal, previous mass vaccination experience, and vaccine diplomacy.

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