The COVID-19 pandemic has disproportionately affected certain groups, such as older people (ie, >65 years), minority ethnic populations, and people with specific chronic conditions including ...diabetes, cardiovascular disease, kidney disease, and some respiratory diseases. There is now evidence of not only direct but also indirect adverse effects of COVID-19 in people with diabetes. Recurrent lockdowns and public health measures throughout the pandemic have restricted access to routine diabetes care, limiting new diagnoses, and affecting self-management, routine follow-ups, and access to medications, as well as affecting lifestyle behaviours and emotional wellbeing globally. Pre-pandemic studies have shown that short-term delays in delivery of routine care, even by 12 months, are associated with adverse effects on risk factor control and worse microvascular, macrovascular, and mortality outcomes in people with diabetes. Disruptions within the short-to-medium term due to natural disasters also result in worse diabetes outcomes. However, the true magnitude of the indirect effects of the COVID-19 pandemic on long-term outcomes and mortality in people with diabetes is still unclear. Disasters tend to exacerbate existing health disparities; as we recover ambulatory diabetes services in the aftermath of the pandemic, there is an opportunity to prioritise those with the greatest need, and to target resources and interventions aimed at improving outcomes and reducing inequality.
The food environment has been implicated as an underlying contributor to the global obesity epidemic. However, few studies have evaluated the relationship between the food environment, dietary ...intake, and overweight/obesity in low- and middle-income countries (LMICs). The aim of this study was to assess the association of full service and fast food restaurant density with dietary intake and overweight/obesity in Delhi, India.
Data are from a cross-sectional, population-based study conducted in Delhi. Using multilevel cluster random sampling, 5364 participants were selected from 134 census enumeration blocks (CEBs). Geographic information system data were available for 131 CEBs (n = 5264) from a field survey conducted using hand-held global positioning system devices. The number of full service and fast food restaurants within a 1-km buffer of CEBs was recorded by trained staff using ArcGIS software, and participants were assigned to tertiles of full service and fast food restaurant density based on their resident CEB. Height and weight were measured using standardized procedures and overweight/obesity was defined as a BMI ≥25 kg/m
.
The most common full service and fast food restaurants were Indian savory restaurants (57.2%) and Indian sweet shops (25.8%). Only 14.1% of full service and fast food restaurants were Western style. After adjustment for age, household income, education, and tobacco and alcohol use, participants in the highest tertile of full service and fast food restaurant density were less likely to consume fruit and more likely to consume refined grains compared to participants in the lowest tertile (both p < 0.05). In unadjusted logistic regression models, participants in the highest versus lowest tertile of full service and fast food restaurant density were significantly more likely to be overweight/obese: odds ratio (95% confidence interval), 1.44 (1.24, 1.67). After adjustment for age, household income, and education, the effect was attenuated: 1.08 (0.92, 1.26). Results were consistent with further adjustment for tobacco and alcohol use, moderate physical activity, and owning a bicycle or motorized vehicle.
Most full service and fast food restaurants were Indian, suggesting that the nutrition transition in this megacity may be better characterized by the large number of unhealthy Indian food outlets rather than the Western food outlets. Full service and fast food restaurant density in the residence area of adults in Delhi, India, was associated with poor dietary intake. It was also positively associated with overweight/obesity, but this was largely explained by socioeconomic status. Further research is needed exploring these associations prospectively and in other LMICs.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
To estimate the prevalence, socio-demographic determinants, common disease combinations, and health impact of multimorbidity among a young rural population.
We conducted a cross-sectional survey ...among participants aged ≥30 years in rural Punjab, North India, from Jan 2019 to April 2019. Multimorbidity was defined as the coexistence of ≥two conditions using a 14-condition tool validated in India. We also calculated a multimorbidity-weighted index (MWI), which provides a weight to each disease based on its impact on physical functioning. Logistic regression was conducted to evaluate the association with sociodemographic variables, mental health (PHQ-9), physical functioning (ADL scale), and self-rated health (SRH).
We analyzed data from 3213 adults Mean age 51.5 (±13), 54% women. Prevalence of single chronic condition, multimorbidity, and MWI was 28.6, 18% and - 1.9 respectively. Age, higher wealth index and ever use alcohol were significantly associated with multimorbidity. Overall, 2.8% of respondents had limited physical functioning, 2.1% had depression, and 61.5% reported low SRH. Poorer health outcomes were more prevalent among the elderly, women, less educated, and those having lower wealth index and multimorbidity, were found to be significantly associated with poor health outcomes.
The burden of multimorbidity was high in this young rural population, which portends significant adverse effects on their health and quality of life. The Indian health system should be reconfigured to address this emerging health priority holistically, by adopting a more integrated and sustainable model of care.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Aims/Introduction
This study aims to evaluate the prevalence of and factors associated with non‐alcoholic fatty liver disease (NAFLD) in Indian women with prior gestational diabetes mellitus (GDM) ...diagnosed using International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria.
Materials and Methods
This cross‐sectional study (2018–2019) enrolled women with and without prior GDM. Study participants underwent detailed assessments, including relevant medical, obstetric and demographic details; 75‐g oral glucose tolerance test with glucose and insulin estimation at 0, 30 and 120 min; and other relevant biochemical and anthropometric measurements. NAFLD status was defined by ultrasonography.
Results
We evaluated a total of 309 women (201 and 108 with and without prior GDM, respectively) at a mean age of 31.9 ± 5.0 years and median of 16 months (interquartile range 9–38 months) following the index delivery. The prevalence of NAFLD was significantly higher in women with prior GDM (62.7% vs 50.0%, P = 0.038; grade 2 and 3 disease, 13.9% vs 6.5%). On logistic regression analysis (fully adjusted model), the odds of NAFLD were 2.11‐fold higher in women with prior GDM (95% confidence interval 1.16–3.85, P = 0.014). Overweight/obesity, metabolic syndrome, prediabetes and homeostasis model of assessment of insulin resistance (a measure of insulin resistance) were positively associated with NAFLD, whereas the Matsuda index (a measure of insulin sensitivity) showed a negative association with NAFLD.
Conclusions
The prevalence of NAFLD is high in women with prior GDM. Such women also have a high burden of cardiometabolic risk factors. Future studies should evaluate the intermediate and long‐term hepatic and cardiovascular risk, and the impact of lifestyle interventions in reducing morbidity in such women.
This study evaluated the prevalence and risk factors of non‐alcoholic fatty liver disease in Indian women with prior gestational diabetes mellitus diagnosed using International Association of Diabetes and Pregnancy Study Groups criteria. Ultrasonography of abdomen was used to define non‐alcoholic fatty liver disease status. Prevalence of non‐alcoholic fatty liver disease was significantly higher in women with prior gestational diabetes mellitus (62.7% vs 50.0%, P = 0.038; grade 2 and 3 disease, 13.9% vs 6.5%).
Background Diabetes control is poor globally and leads to burdensome microvascular and macrovascular complications. We aimed to assess post hoc between-group differences in sustained risk factor ...control and macrovascular and microvascular endpoints at 6.5 years in the Center for cArdiovascular Risk Reduction in South Asia (CARRS) randomized trial. Methods and findings This parallel group individual randomized clinical trial was performed at 10 outpatient diabetes clinics in India and Pakistan from January 2011 through September 2019. A total of 1,146 patients with poorly controlled type 2 diabetes (HbA1c ≥8% and systolic BP ≥140 mm Hg and/or LDL-cholesterol ≥130 mg/dL) were randomized to a multicomponent quality improvement (QI) strategy (trained nonphysician care coordinator to facilitate care for patients and clinical decision support system for physicians) or usual care. At 2.5 years, compared to usual care, those receiving the QI strategy were significantly more likely to achieve multiple risk factor control. Six clinics continued, while 4 clinics discontinued implementing the QI strategy for an additional 4-year follow-up (overall median 6.5 years follow-up). In this post hoc analysis, using intention-to-treat, we examined between-group differences in multiple risk factor control (HbA1c <7% plus BP <130/80 mm Hg and/or LDL-cholesterol <100 mg/dL) and first macrovascular endpoints (nonfatal myocardial infarction, nonfatal stroke, death, revascularization angioplasty or coronary artery bypass graft), which were co-primary outcomes. We also examined secondary outcomes, namely, single risk factor control, first microvascular endpoints (retinopathy, nephropathy, neuropathy), and composite first macrovascular plus microvascular events (which also included amputation and all-cause mortality) by treatment group and whether QI strategy implementation was continued over 6.5 years. At 6.5 years, assessment data were available for 854 participants (74.5%; n = 417 intervention; n = 437 usual care). In terms of sociodemographic and clinical characteristics, participants in the intervention and usual care groups were similar and participants at sites that continued were no different to participants at sites that discontinued intervention implementation. Patients in the intervention arm were more likely to exhibit sustained multiple risk factor control than usual care (relative risk: 1.77; 95% confidence interval CI, 1.45, 2.16), p < 0.001. Cumulatively, there were 233 (40.5%) first microvascular and macrovascular events in intervention and 274 (48.0%) in usual care patients (absolute risk reduction: 7.5% 95% CI: −13.2, −1.7, p = 0.01; hazard ratio HR = 0.72 95% CI: 0.61, 0.86), p < 0.001. Patients in the intervention arm experienced lower incidence of first microvascular endpoints (HR = 0.68 95% CI: 0.56, 0.83), p < 0.001, but there was no evidence of between-group differences in first macrovascular events. Beneficial effects on microvascular and composite vascular outcomes were observed in sites that continued, but not sites that discontinued the intervention. Conclusions In urban South Asian clinics, a multicomponent QI strategy led to sustained multiple risk factor control and between-group differences in microvascular, but not macrovascular, endpoints. Between-group reductions in vascular outcomes at 6.5 years were observed only at sites that continued the QI intervention, suggesting that practice change needs to be maintained for better population health of people with diabetes. Trial registration ClinicalTrials.gov NCT01212328 .
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Indians undergoing socioeconomic and lifestyle transitions will be maximally affected by epidemic of type 2 diabetes (T2D). We conducted a two-stage genome-wide association study of T2D in 12,535 ...Indians, a less explored but high-risk group. We identified a new type 2 diabetes-associated locus at 2q21, with the lead signal being rs6723108 (odds ratio 1.31; P = 3.32 × 10⁻⁹). Imputation analysis refined the signal to rs998451 (odds ratio 1.56; P = 6.3 × 10⁻¹²) within TMEM163 that encodes a probable vesicular transporter in nerve terminals. TMEM163 variants also showed association with decreased fasting plasma insulin and homeostatic model assessment of insulin resistance, indicating a plausible effect through impaired insulin secretion. The 2q21 region also harbors RAB3GAP1 and ACMSD; those are involved in neurologic disorders. Forty-nine of 56 previously reported signals showed consistency in direction with similar effect sizes in Indians and previous studies, and 25 of them were also associated (P < 0.05). Known loci and the newly identified 2q21 locus altogether explained 7.65% variance in the risk of T2D in Indians. Our study suggests that common susceptibility variants for T2D are largely the same across populations, but also reveals a population-specific locus and provides further insights into genetic architecture and etiology of T2D.
There is substantial interest in leveraging digital health technology to support hypertension management in low- and middle-income countries such as India. The potential for healthcare infrastructure ...and broader context to support such initiatives in India has not been examined. We evaluated existing healthcare infrastructure to support digital health interventions and examined epidemiologic, socioeconomic, and geographical contextual correlates of healthcare infrastructure in 544 districts covering 29 states and union territories across India.
The study was a cross-sectional analysis of India's Fourth District Level Household and Facility Survey (DLHS-4; 2012-2014), the most up-to-date nationally representative district-level healthcare infrastructure data. Facilities were the unit of analysis, and analyses accounted for clustering within states. The main outcome was healthcare system infrastructural context to implement hypertension management programs. Domains included diagnostics (functional BP instrument), medications (anti-hypertensive medication in stock), essential clinical staff (e.g., staff nurse, medical officer, pharmacist), and IT specific infrastructure (regular power supply, internet connection, computer availability). Descriptive analysis was conducted for infrastructure indicators based on the Indian Public Health Standards, and logistic regression was conducted to estimate the association between epidemiologic and geographical context (exposures) and the composite measure of healthcare system.
Data from 32,215 government facilities were analyzed. Among lowest-tier subcenters, 30% had some IT infrastructure, while at the highest-tier district hospitals, 92% possessed IT infrastructure. At mid-tier primary health centres and community health centres, IT infrastructure availability was 28 and 51%, respectively. For all but sub-centres, the availability of essential staff was lower than the availability of IT infrastructure. For all but district hospitals, higher levels of blood pressure, body mass index, and urban residents were correlated with more favorable infrastructure. By region, districts in Western India tended towards having the best prepared health facilities.
IT infrastructure to support digital health interventions is more frequently lacking at lower and mid-tier healthcare facilities compared with apex facilities in India. Gaps were generally larger for staffing than physical infrastructure, suggesting that beyond IT infrastructure, shortages in essential staff impose significant constraints to the adoption of digital health interventions. These data provide early benchmarks for state- and district-level planning.
Celotno besedilo
Dostopno za:
CEKLJ, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Cardiometabolic diseases are increasing disproportionately in South Asia compared with other regions of the world despite high levels of vegetarianism. This unexpected discordance may be explained by ...differences in the healthfulness of vegetarian and non-vegetarian diets in South Asia compared with the United States. The aim of this study was to compare the food group intake of vegetarians with non-vegetarians in South Asia and the United States and to evaluate associations between vegetarianism and cardiometabolic disease risk factors (overweight/obesity, central obesity, diabetes, hypertension, high triacylglycerols, high low-density lipoprotein, low high-density lipoprotein, and high Framingham Heart Score).
Using cross-sectional data from adults (age 20–69 y) in South Asia (Centre for Cardiometabolic Risk Reduction in South-Asia CARRS 2010–2011; N = 15 665) and the United States (National Health and Nutrition Examination Survey 2003–2006; N = 2159), adherence to a vegetarian diet was assessed using food propensity questionnaires. Multivariable logistic regression was used to estimate odds ratios and predicted margins (e.g., adjusted prevalence of the outcomes).
One-third (33%; n = 4968) of adults in the South Asian sample were vegetarian compared with only 2.4% (n = 59) in the US sample. Among South Asians, vegetarians more frequently ate dairy, legumes, vegetables, fruit, desserts, and fried foods than non-vegitarians (all P < 0.05). Among Americans, vegetarians more frequently ate legumes, fruit, and whole grains, and less frequently ate refined cereals, desserts, fried foods, fruit juice, and soft drinks than non-vegetarians (all P < 0.05). After adjustment for confounders (age, sex, education, tobacco, alcohol, and also city in CARRS), South Asian vegetarians were slightly less frequently overweight/obese compared with non-vegetarians: 49% (95% confidence interval CI, 45%–53%) versus 53% (95% CI, 51%–56%), respectively; whereas US vegetarians were considerably less frequently overweight/obese compared with non-vegetarians: 48% (95% CI, 32%–63%) versus 68% (95% CI, 65%–70%), respectively. Furthermore, US vegetarians were less likely to exhibit central obesity than non-vegetarians: 62% (95% CI, 43%–78%) versus 78% (95% CI, 76%–80%), respectively.
There is greater divergence between vegetarian and non-vegetarian diets in the United States than in South Asia, and US vegetarians have more consistently healthier food group intakes than South Asian vegetarians. Vegetarians in both populations have a lower probability of overweight/obesity compared with non-vegetarians. The strength of this association may be stronger for US vegetarian diets, which were also protective against central obesity.
•To our knowledge, this was the first study to explore vegetarian diets in both the United States and South Asia.•We used large representative samples and defined vegetarianism with food propensity data.•Vegetarians had a lower probability of overweight/obesity in both populations.•The strength of this association may be stronger for US vegetarian diets.•Results inform lifestyle interventions and policies for chronic disease prevention.
The growing burden of hypertension and diabetes is one of the major public health challenges being faced by the health system in India. Clinical Decision Support Systems (CDSS) that assist with ...tailoring evidence-based management approaches combined with task-shifting from more specialized to less specialized providers may together enhance the impact of a program. We sought to integrate a technology "CDSS" and a strategy "Task-shifting" within the Government of India's (GoI) Non-Communicable Diseases (NCD) System under the Comprehensive Primary Health Care (CPHC) initiative to enhance the program's impact to address the growing burden of hypertension and diabetes in India.
We developed a model of care "I-TREC" entirely calibrated for implementation within the current health system across all facility types (Primary Health Centre, Community Health Centre, and District Hospital) in a block in Shaheed Bhagat Singh (SBS) Nagar district of Punjab, India. We undertook an academic-community partnership to incorporate the combination of a CDSS with task-shifting into the GoI CPHC-NCD system, a platform that assists healthcare providers to record patient information for routine NCD care. Academic partners developed clinical algorithms, a revised clinic workflow, and provider training modules with iterative collaboration and consultation with government and technology partners to incorporate CDSS within the existing system.
The CDSS-enabled GoI CPHC-NCD system provides evidence-based recommendations for hypertension and diabetes; threshold-based prompts to assure referral mechanism across health facilities; integrated patient database, and care coordination through workflow management and dashboard alerts. To enable efficient implementation, modifications were made in the patient workflow and the fulcrum of the use of technology shifted from physician to nurse.
Designed to be applicable nationwide, the I-TREC model of care is being piloted in a block in the state of Punjab, India. Learnings from I-TREC will provide a roadmap to other public health experts to integrate and adapt their interventions at the national level.
CTRI/2020/01/022723.
Celotno besedilo
Dostopno za:
CEKLJ, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Previous epidemiological studies, largely conducted in high-income countries and cross-sectional, have suggested a relatively strong association between exposure to dichlorodiphenyldichloroethylene ...(DDE), a metabolite of the pesticide dichlorodiphenyltrichloroethane (DDT), and type 2 diabetes. DDT is widely used in India and the prevalence of type 2 diabetes there is increasing, but the association between these factors has not been explored to date.
The objective was to estimate the association of the p,p′ isomer of DDE with incident type 2 diabetes in India.
A nested case-control study was conducted in a representative prospective cohort of adults from two cities in India. Participants were enrolled in 2010–11 (n = 12,271) and followed for annual assessment of chronic diseases including type 2 diabetes. Baseline plasma samples from incident cases of diabetes (n = 193) and sex-city-matched controls (n = 323) were selected for analysis of p,p-DDE. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression.
At baseline, cases had higher p,p-DDE concentrations: geometric mean (95% CI) 330 (273–399) ng/g lipid compared to 223 (189–262) ng/g lipid among controls. Delhi participants had higher p,p-DDE concentrations: 579 (521–643) ng/g lipid compared to 122 (102–145) ng/g lipid in Chennai. In unadjusted models, being in the highest versus lowest quartile of p,p-DDE was associated with a more than doubling of the odds of diabetes: unadjusted OR (95% CI), 2.30 (1.19, 4.43). However, this effect was no longer significant after adjustment for age: adjusted (95% CI), 0.97 (0.46, 2.06).
Results suggest that levels of p,p′-DDE in Delhi are exceptionally high, but we did not observe a significant association between p,p-DDE and incident type 2 diabetes. As this is the first study to evaluate this association in India, more studies are needed to inform our understanding of the association in this context, including potential routes of exposure.
•First study of the association between plasma DDE concentration and incident diabetes in India•Strengths include prospective study design, direct measurement of p,p-DDE, and well-characterised metabolic status•Levels of p,p’-DDE in Delhi are exceptionally high; levels are lower in the southern, coastal city of Chennai•We did not observe a significant association between p,p-DDE and incident type 2 diabetes•BMI was much lower than reported in previous studies; more research is needed on how the DDE-diabetes relationship changes over time in developing countries
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