Shah Ebrahim and colleagues examine the distribution of obesity, diabetes, and other cardiovascular risk factors among urban migrant factory workers in India, together with their rural siblings. The investigators identify patterns of change of cardiovascular risk factors associated with urban migration.

Objectives To investigate the sociodemographic patterning of non-communicable disease risk factors in rural India. Design Cross sectional study. Setting About 1600 villages from 18 states in India. Most were from four large states due to a convenience sampling strategy. Participants 1983 (31% women) people aged 20-69 years (49% response rate). Main outcome measures Prevalence of tobacco use, alcohol use, low fruit and vegetable intake, low physical activity, obesity, central adiposity, hypertension, dyslipidaemia, diabetes, and underweight. Results Prevalence of most risk factors increased with age. Tobacco and alcohol use, low intake of fruit and vegetables, and underweight were more common in lower socioeconomic positions; whereas obesity, dyslipidaemia, and diabetes (men only) and hypertension (women only) were more prevalent in higher socioeconomic positions. For example, 37% (95% CI 30% to 44%) of men smoked tobacco in the lowest socioeconomic group compared with 15% (12% to 17%) in the highest, while 35% (30% to 40%) of women in the highest socioeconomic group were obese compared with 13% (7% to 19%) in the lowest. The age standardised prevalence of some risk factors was: tobacco use (40% (37% to 42%) men, 4% (3% to 6%) women); low fruit and vegetable intake (69% (66% to 71%) men, 75% (71% to 78%) women); obesity (19% (17% to 21%) men, 28% (24% to 31%) women); dyslipidaemia (33% (31% to 36%) men, 35% (31% to 38%) women); hypertension (20% (18% to 22%) men, 22% (19% to 25%) women); diabetes (6% (5% to 7%) men, 5% (4% to 7%) women); and underweight (21% (19% to 23%) men, 18% (15% to 21%) women). Risk factors were generally more prevalent in south Indians compared with north Indians. For example, the prevalence of dyslipidaemia was 21% (17% to 33%) in north Indian men compared with 33% (29% to 38%) in south Indian men, while the prevalence of obesity was 13% (9% to 17%) in north Indian women compared with 24% (19% to 30%) in south Indian women. ConclusionsThe prevalence of most risk factors was generally high across a range of sociodemographic groups in this sample of rural villagers in India; in particular, the prevalence of tobacco use in men and obesity in women was striking. However, given the limitations of the study (convenience sampling design and low response rate), cautious interpretation of the results is warranted. These data highlight the need for careful monitoring and control of non-communicable disease risk factors in rural areas of India. INTRODUCTIONThe current epidemic of non-communicable diseases in India is attributed to increased longevity and lifestyle changes resulting from urbanisation.1 2 However, recent data suggest that non-communicable diseases are already the commonest cause of death in some parts of rural India. [3][4][5] This is plausible as, apart from improvements in life expectancy, the greater interconnectedness increasingly allows rural populations to adopt urban lifestyles without migration to urban areas. [5][6][7] A rise in the prevalence of non-communicable dise...

Introduction The coronavirus pandemic has affected more than 20 million people so far. Elevated cytokines and suppressed immune responses have been hypothesized to set off a cytokine storm, contributing to ARDS, multiple‐organ failure and, in the most severe cases, death. We aimed to quantify the differences in the circulating levels of major inflammatory and immunological markers between severe and nonsevere COVID‐19 patients. Methods Relevant studies were identified from PubMed, EMBASE, Web of Science, SCOPUS and preprint servers. Risk of bias was assessed for each study, using appropriate checklists. All studies were described qualitatively and a subset was included in the meta‐analysis, using forest plots. Results Based on 23 studies, mean cytokine levels were significantly higher (IL‐6: MD, 19.55 pg/mL; CI, 14.80, 24.30; IL‐8: MD, 19.18 pg/mL; CI, 2.94, 35.43; IL‐10: MD, 3.66 pg/mL; CI, 2.41, 4.92; IL‐2R: MD, 521.36 U/mL; CI, 87.15, 955.57; and TNF‐alpha: MD, 1.11 pg/mL; CI, 0.07, 2.15) and T‐lymphocyte levels were significantly lower (CD4+ T cells: MD, −165.28 cells/µL; CI, −207.58, −122.97; CD8+ T cells: MD, −106.51 cells/µL; CI, −128.59, −84.43) among severe cases as compared to nonsevere ones. There was heterogeneity across studies due to small sample sizes and nonuniformity in outcome assessment and varied definitions of disease severity. The overall quality of studies was sub‐optimal. Conclusion Severe COVID‐19 is characterized by significantly increased levels of pro‐inflammatory cytokines and reduced T lymphocytes. Well‐designed and adequately powered prospective studies are needed to amplify the current evidence and provide definitive answers to dilemmas regarding timing and type of anti‐COVID‐19 therapy particularly in severe patients.

BackgroundThe relation of serum uric acid (SUA) with systemic inflammation has been little explored in humans and results have been inconsistent. We analyzed the association between SUA and circulating levels of interleukin-6 (IL-6), interleukin-1β (IL-1β), tumor necrosis factor- α (TNF-α) and C-reactive protein (CRP).Methods and FindingsThis cross-sectional population-based study conducted in Lausanne, Switzerland, included 6085 participants aged 35 to 75 years. SUA was measured using uricase-PAP method. Plasma TNF-α, IL-1β and IL-6 were measured by a multiplexed particle-based flow cytometric assay and hs-CRP by an immunometric assay. The median levels of SUA, IL-6, TNF-α, CRP and IL-1β were 355 µmol/L, 1.46 pg/mL, 3.04 pg/mL, 1.2 mg/L and 0.34 pg/mL in men and 262 µmol/L, 1.21 pg/mL, 2.74 pg/mL, 1.3 mg/L and 0.45 pg/mL in women, respectively. SUA correlated positively with IL-6, TNF-α and CRP and negatively with IL-1β (Spearman r: 0.04, 0.07, 0.20 and 0.05 in men, and 0.09, 0.13, 0.30 and 0.07 in women, respectively, P<0.05). In multivariable analyses, SUA was associated positively with CRP (β coefficient ± SE = 0.35±0.02, P<0.001), TNF-α (0.08±0.02, P<0.001) and IL-6 (0.10±0.03, P<0.001), and negatively with IL-1β (−0.07±0.03, P = 0.027). Upon further adjustment for body mass index, these associations were substantially attenuated.ConclusionsSUA was associated positively with IL-6, CRP and TNF-α and negatively with IL-1β, particularly in women. These results suggest that uric acid contributes to systemic inflammation in humans and are in line with experimental data showing that uric acid triggers sterile inflammation.