Introduction . Hypertension is one of the most important modifiable risk factors for cardiovascular diseases. The objective of this study is to estimate the prevalence, awareness, treatment, and control of hypertension and its associated risk factors in Ernakulam district, Kerala. Methods . In this prospective family‐based cohort study, 573 families were included with a total of 997 participants aged 30 years and above. Baseline interviews were conducted in participant’s homes using a combination of self‐structured and standardized questionnaire. Blood pressure and plasma glucose were assessed for each participant. Results . The prevalence of hypertension was 43%. It was slightly higher in women than men (43.7% vs. 41.4%). The mean systolic blood pressure in the hypertensive population was 141.9 mmHg and mean diastolic blood pressure was 85.3 mmHg. In total, 78% (86.2% in women, 62.9% in men) of the participants were aware of their hypertension. Among those aware, 60.4% (63.5% in women, 52.6% in men) of the participants were on treatment, and hypertension was controlled in 75.1% (77.5% women, 68% in men) of the participants on treatment. The prevalence of hypertension was higher among persons with comorbidities (diabetes 64.5%, transient ischemic attack 54.7%, and heart disease 64.4%). Prevalence was lower among persons who did regular vigorous intensity exercise versus those who did moderate intensity exercise (32% vs. 45.7%) and among nonsmokers versus smokers (42.2% vs. 46.6%). Conclusion . The prevalence of hypertension in Kerala is high. Although awareness is quite high, there is a need to improve the number of persons with hypertension taking treatment.

Caregivers of people with disability experience difficulties in a variety of care domains. Understanding the predictive factors of caregiver strain is important in developing and implementing evide...

Background: Problematic use of the internet (PUI) is a growing concern, particularly in the young population. Family factors influence internet use among children in negative ways. This study examined the existing literature on familial or parental factors related to PUI in children. Methods: A scoping review was conducted in EBSCOhost, PubMed, ScienceDirect, JSTOR, Biomed Central, VHL Regional Portal, Cochrane Library, Emerald Insight, and Oxford Academic Journal databases. Studies reporting data on family factors associated with PUI in children, published in English in the 10 years to July 2020 were included. The following data were extracted from each paper by two independent reviewers: methodology and demographic, familial, psychiatric, and behavioral correlates of PUI in children. Results: Sixty-nine studies fulfilled the eligibility criteria. Three themes emerged: parenting, parental mental health, and intrafamilial demographic correlates of PUI in children. Parenting styles, parental mediation, and parent–child attachment were the major parenting correlates. Conclusion: Literature on significant familial and parental factors associated with PUI in children is scarce. More research is required to identify the interactions of familial and parental factors with PUI in children, to develop informed management strategies to address this issue.

Background: This study is a low-cost community mental health task-sharing model driven by university students to strengthen the mental health workforce in poor resource settings. This article presents the feasibility of a stepped referral model using the community health workforce and university students. The primary feasibility objective is to detect and refer people with mental illness from the community using a task-sharing approach. Methods: We tested the model using a cross-sectional, one-phase door-knock survey in three geographically defined locations in Kerala, India, between May and July 2019. Students surveyed 549 residents above 18 years of age who consented to participate in the study to detect depressive symptoms and suicidality. The feasibility of the current model was evaluated based on four criteria: (a) identification and deployment of untapped human resources, (b) coordination of community health resources, (c) the acceptability of stepped referral pathways, and (d) identification of implementation challenges. Results: The mean age of the participants was 38.8, and more than 62% of the respondents were women. The results showed that 11.29%, 8.38%, and 4.91% of people reported mild, moderate, and severe levels of depression, respectively, and suicidal thoughts were found in 6.9% and suicidal ideation in 1.8%. The odds of depression were higher among females compared to males (OR: 1.64 (0.75–2.52), poor people (OR: 2.01 (1.14–2.88), and people with chronic illnesses (OR: 2.03 (1.24–2.81). The agreement of the findings with professional-administered research validated the strategy’s efficiency. Twenty-seven patients with severe/extreme degrees of depression were sent for high-intensity interventions led by the mental health team, whereas 135 individuals with mild and above depression were referred for low-intensity interventions. Conclusions: The newly recruited mental health workforce-driven screenings were acceptable and effective in detecting mental illness in the community population. We tested the care coordination systems and processes in creating referral pathways for the detected patients. Further, task-sharing stepped referral model will be tested in five panchayats (the lowest tier of local self-government) before replicating the model across India through Unnat Bharat Abhiyan (UBA) scheme.

Objectives The purpose of this study is to examine the existing literature of the major social risk factors which are associated with diabetes, hypertension and the comorbid conditions of depression and anxiety in India. Design Scoping review. Data sources Scopus, Embase, CINAHL Plus, PsycINFO, Web of Science and MEDLINE were searched for through September 2019. Eligibility criteria for selecting studies Studies reporting data on social risk factors for diabetes or hypertension and depression or anxiety in community-based samples of adults from India, published in English in the 10 years to 2019, were included. Studies that did not disaggregate pooled data from other countries were excluded. Data extraction and synthesis Two independent reviewers extracted study aims; methods; sample size and description; demographic, social and behavioural risk factors and a summary of findings from each paper. Risk factors were synthesised into six emergent themes. Results Ten studies were considered eligible and included in this review. Nine presented cross-sectional data and one was a qualitative case study. Six themes emerged, that is, demographic factors, economic aspects, social networks, life events, health barriers and health risk behaviours. Conclusions Literature relating to the major social risk factors associated with diabetes, hypertension and comorbid depression and anxiety in India is sparse. More research is required to better understand the interactions of social context and social risk factors with non-communicable diseases and comorbid mental health problems so as to better inform management of these in the Indian subcontinent.

Background: Cardiovascular disease (CVD) is the leading cause of mortality in India. Social and behavioural factors are strongly interrelated in the prevention and control of CVD. The ability to make lifestyle changes to control hypertension and diabetes (major risk factors for CVD) is determined by factors such as education, gender, caste, poverty, and urbanicity. This study aimed to improve our understanding of the inter-relationship of social and behavioural factors in the management of elevated serum glucose and high blood pressure and co-morbid mental health conditions.Methods: A population-based catchment area cross sectional survey was conducted in Kerala, India. Data were collected from residents aged over 30 years (n = 997) using standardized tools and clinical measures. We performed latent class analysis incrementally to extract homogeneous latent classes of individuals based on their responses to social and behavioural risk factors in the survey. Using structural equation models, we assessed the mediating effect of depression and anxiety, and social or behavioural risk factors, on management of high blood pressure and raised serum glucose levels.Results: The prevalence of high blood pressure and blood glucose in the sample was 33 and 26% respectively. Latent class analysis found three clusters of risk factors. One had a predominance of behavioural characteristics, another of social risk factors and the third was a low risk group. Age, female sex, and marital status had an effect on high blood pressure and high glucose, though were mediated by mental health, social and behavioural risk factors.Conclusions: Interventions to improve the management of risk factors for CVD need to address social risk factors and be sensitive to the needs of population sub-groups that may require additional support to access health services. An integration of social and health services may be required to achieve this.