SummaryBackground18% of the world's population lives in India, and many states of India have populations similar to those of large countries. Action to effectively improve population health in India requires availability of reliable and comprehensive state-level estimates of disease burden and risk factors over time. Such comprehensive estimates have not been available so far for all major diseases and risk factors. Thus, we aimed to estimate the disease burden and risk factors in every state of India as part of the Global Burden of Disease (GBD) Study 2016.MethodsUsing all available data sources, the India State-level Disease Burden Initiative estimated burden (metrics were deaths, disability-adjusted life-years [DALYs], prevalence, incidence, and life expectancy) from 333 disease conditions and injuries and 84 risk factors for each state of India from 1990 to 2016 as part of GBD 2016. We divided the states of India into four epidemiological transition level (ETL) groups on the basis of the ratio of DALYs from communicable, maternal, neonatal, and nutritional diseases (CMNNDs) to those from non-communicable diseases (NCDs) and injuries combined in 2016. We assessed variations in the burden of diseases and risk factors between ETL state groups and between states to inform a more specific health-system response in the states and for India as a whole.FindingsDALYs due to NCDs and injuries exceeded those due to CMNNDs in 2003 for India, but this transition had a range of 24 years for the four ETL state groups. The age-standardised DALY rate dropped by 36·2% in India from 1990 to 2016. The numbers of DALYs and DALY rates dropped substantially for most CMNNDs between 1990 and 2016 across all ETL groups, but rates of reduction for CMNNDs were slowest in the low ETL state group. By contrast, numbers of DALYs increased substantially for NCDs in all ETL state groups, and increased significantly for injuries in all ETL state groups except the highest. The all-age prevalence of most leading NCDs increased substantially in India from 1990 to 2016, and a modest decrease was recorded in the age-standardised NCD DALY rates. The major risk factors for NCDs, including high systolic blood pressure, high fasting plasma glucose, high total cholesterol, and high body-mass index, increased from 1990 to 2016, with generally higher levels in higher ETL states; ambient air pollution also increased and was highest in the low ETL group. The incidence rate of the leading causes of injuries also increased from 1990 to 2016. The five leading individual causes of DALYs in India in 2016 were ischaemic heart disease, chronic obstructive pulmonary disease, diarrhoeal diseases, lower respiratory infections, and cerebrovascular disease; and the five leading risk factors for DALYs in 2016 were child and maternal malnutrition, air pollution, dietary risks, high systolic blood pressure, and high fasting plasma glucose. Behind these broad trends many variations existed between the ETL state groups and between states within the ETL groups. Of the ten le...

SummaryBackgroundThe burden of diabetes is increasing rapidly in India but a systematic understanding of its distribution and time trends is not available for every state of India. We present a comprehensive analysis of the time trends and heterogeneity in the distribution of diabetes burden across all states of India between 1990 and 2016.MethodsWe analysed the prevalence and disability-adjusted life-years (DALYs) of diabetes in the states of India from 1990 to 2016 using all available data sources that could be accessed as part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, and assessed heterogeneity across the states. The states were placed in four groups based on epidemiological transition level (ETL), defined on the basis of the ratio of DALYs from communicable diseases to those from non-communicable diseases and injuries combined, with a low ratio denoting high ETL and vice versa. We assessed the contribution of risk factors to diabetes DALYs and the relation of overweight (body-mass index 25 kg/m2 or more) with diabetes prevalence. We calculated 95% uncertainty intervals (UIs) for the point estimates.FindingsThe number of people with diabetes in India increased from 26·0 million (95% UI 23·4–28·6) in 1990 to 65·0 million (58·7–71·1) in 2016. The prevalence of diabetes in adults aged 20 years or older in India increased from 5·5% (4·9–6·1) in 1990 to 7·7% (6·9–8·4) in 2016. The prevalence in 2016 was highest in Tamil Nadu and Kerala (high ETL) and Delhi (higher-middle ETL), followed by Punjab and Goa (high ETL) and Karnataka (higher-middle ETL). The age-standardised DALY rate for diabetes increased in India by 39·6% (32·1–46·7) from 1990 to 2016, which was the highest increase among major non-communicable diseases. The age-standardised diabetes prevalence and DALYs increased in every state, with the percentage increase among the highest in several states in the low and lower-middle ETL state groups. The most important risk factor for diabetes in India was overweight to which 36·0% (22·6–49·2) of the diabetes DALYs in 2016 could be attributed. The prevalence of overweight in adults in India increased from 9·0% (8·7–9·3) in 1990 to 20·4% (19·9–20·8) in 2016; this prevalence increased in every state of the country. For every 100 overweight adults aged 20 years or older in India, there were 38 adults (34–42) with diabetes, compared with the global average of 19 adults (17–21) in 2016.InterpretationThe increase in health loss from diabetes since 1990 in India is the highest among major non-communicable diseases. With this increase observed in every state of the country, and the relative rate of increase highest in several less developed low ETL states, policy action that takes these state-level differences into account is needed urgently to control this potentially explosive public health situation.FundingBill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.

Alkali supplementation to increase venous bicarbonate levels to 24-26 mEq/L is associated with preservation of LBM and kidney function in patients with CKD stages 3 and 4.

Community-acquired acute kidney injury (AKI) in developing tropical countries is markedly different from AKI in developed countries with a temperate climate, which exemplifies the influence that environment can have on the epidemiology of human diseases. The aetiology and presentation of AKI reflect the ethnicity, socioeconomic factors, climatic and ecological characteristics in tropical countries. Tropical zones are characterized by high year-round temperatures and the absence of frost, which supports the propagation of infections that can cause AKI, including malaria, leptospirosis, HIV and diarrhoeal diseases. Other major causes of AKI in tropical countries are envenomation; ingestion of toxic herbs or chemicals; poisoning; and obstetric complications. These factors are associated with low levels of income, poor access to treatment, and social or cultural practices (such as the use of traditional herbal medicines and treatments) that contribute to poor outcomes of patients with AKI. Most causes of AKI in developing tropical countries are preventable, but strategies to improve the outcomes and reduce the burden of tropical AKI require both improvements in basic public health, achieved through effective interventions, and increased access to effective medical care (especially for patients with established AKI).

Context. Sampling blood for serum analysis is an invasive procedure. A noninvasive alternative would be beneficial to patients and health care professionals. Aim. To correlate serum and salivary creatinine levels and evaluate the role of saliva as a noninvasive alternative to serum for creatinine estimation in chronic kidney disease patients. Study Design. Case-control study. Methods. Blood and saliva samples were collected from 37 healthy individuals and 105 chronic kidney disease patients. Serum and salivary creatinine levels were estimated using automatic analyser. Statistical Analysis. The serum and salivary creatinine levels between controls and cases were compared using t-test. Correlation between serum and salivary creatinine was obtained in controls and cases using Pearson correlation coefficient. Receiver operating characteristic analysis was done to assess the diagnostic performance of salivary creatinine. Cut-off values were established for salivary creatinine. Results. Serum and salivary creatinine levels were significantly higher in CKD patients than controls. The correlation was negative in controls and positive in cases. Area under the curve for salivary creatinine was found to be 0.967. A cut-off value of 0.2 mg/dL gave a sensitivity of 97.1% and specificity of 86.5%. Conclusion. Saliva can be used as a noninvasive alternative to serum for creatinine estimation.