RESUMO
Background: Patients with dementia usually have multiple comorbidities. The presence of comorbidities may exacerbate the progression of dementia and decreases the patient's ability to participate in health maintenance activities. However, there is hardly any meta-analysis estimating the magnitude of comorbidities among patients with dementia in the Indian context. Methods: We searched PubMed, Scopus, and Google Scholar, and relevant studies conducted in India were included. The risk of bias was assessed and a random-effects meta-analysis model was used in which I2 statistics were calculated to measure heterogeneity among studies. Results: Fourteen studies were included in the meta-analysis based on the inclusion and exclusion criteria. Altogether, we found the coexistence of comorbid conditions such as hypertension (51.10%), diabetes (27.58%), stroke (15.99%), and factors like tobacco use (26.81 %) and alcohol use (9.19%) among patients with dementia in this setting. The level of heterogeneity was high due to differences in the methodologies in the included studies. Conclusions: Our study found hypertension as the most common comorbid condition among patients with dementia in India. The observed lacuna of methodological limitations in the studies included in the current meta-analysis provides the urgent need for good quality research to successfully meet the challenges ahead while devising appropriate strategies to treat the comorbidities among patients with dementia.
RESUMO
Background: The burden of stroke is increasing in India, but there is limited understanding of the distribution of reported risk factors in the Indian setting. It is vital to generate robust data on these modifiable risk factors to scale up appropriate strategies for the prevention of cerebrovascular diseases in this setting. Summary: The objective of this study is to estimate the overall proportion of life style risk factors of patients with stroke in the Indian setting. We searched PubMed and Google Scholar and relevant studies published till February 2022 were included. The risk of bias assessment was considered for the study selection criterion in the meta-analysis. The publication bias was evaluated by funnel plots and Egger's test. We identified 61 studies in the systematic review and after quality assessment, 36 studies were included for meta-analysis. Random effect model was used due to the significant inconsistency among the included studies (I2 > 97%). The mean age of the participants was 53.84±9.3 years and patients with stroke were predominantly males (64%). Hypertension (56.69%; 95% CI: - 48.45 - 64.58), obesity (36.61%; 95% CI: - 19.31 - 58.23), dyslipidemia (30.6%; 95% CI: - 22 - 40.81) and diabetes mellitus (23.8%; 95% CI: - 18.79 - 29.83) are the leading intermediate conditions associated with stroke. The Physical inactivity - 29.9% (95% CI: - 22.9 - 37.1), history of tobacco use (28.59 %; 95% CI: - 22.22 - 32.94) and alcohol use (28.15 %; 95% CI: - 20.49 - 37.33) were reported as the behavioral risk factors for stroke in this setting. Key Messages: The current meta-analysis provides robust estimates of the life style related risk-factor of stroke in India based on the observational studies conducted from 1994 to 2019. Estimating the pooled analysis of stroke risk factors is crucial to predict the imposed burden of the illness and ascertain the treatment and prevention strategies for controlling the modifiable risk factors in this setting.
RESUMO
BACKGROUND: Among the core principles of the 2030 agenda of Sustainable Development Goals (SDGs) is the call to Leave no One behind (LNOB), a principle that gained resonance as the world contended with the COVID-19 pandemic. The south Indian state of Kerala received acclaim globally for its efforts in managing COVID-19 pandemic. Less attention has been paid, however, to how inclusive this management was, as well as if and how those "left behind" in testing, care, treatment, and vaccination efforts were identified and catered to. Filling this gap was the aim of our study. METHODS: We conducted In-depth interviews with 80 participants from four districts of Kerala from July to October 2021. Participants included elected local self-government members, medical and public health staff, as well as community leaders. Following written informed consent procedures, each interviewee was asked questions about whom they considered the most "vulnerable" in their areas. They were also asked if there were any special programmes/schemes to support the access of "vulnerable" groups to general and COVID related health services, as well as other needs. Recordings were transliterated into English and analysed thematically by a team of researchers using ATLAS.ti 9.1 software. RESULTS: The age range of participants was between 35 and 60 years. Vulnerability was described differentially by geography and economic context; for e.g., fisherfolk were identified in coastal areas while migrant labourers were considered as vulnerable in semi-urban areas. In the context of COVID-19, some participants reflected that everyone was vulnerable. In most cases, vulnerable groups were already beneficiaries of various government schemes within and beyond the health sector. During COVID, the government prioritized access to COVID-19 testing and vaccination among marginalized population groups like palliative care patients, the elderly, migrant labourers, as well as Scheduled Caste and Scheduled Tribes communities. Livelihood support like food kits, community kitchen, and patient transportation were provided by the LSGs to support these groups. This involved coordination between health and other departments, which may be formalised, streamlined and optimised in the future. CONCLUSION: Health system actors and local self-government members were aware of vulnerable populations prioritized under various schemes but did not describe vulnerable groups beyond this. Emphasis was placed on the broad range of services made available to these "left behind" groups through interdepartmental and multi-stakeholder collaboration. Further study (currently underway) may offer insights into how these communities - identified as vulnerable - perceive themselves, and whether/how they receive, and experience schemes designed for them. At the program level, inclusive and innovative identification and recruitment mechanisms need to be devised to identify populations who are currently left behind but may still be invisible to system actors and leaders.