Correlates of diabetes mellitus and hypertension in India: Change as evidenced from NFHS- 4 and 5 during 2015-2021.

Both diabetes mellitus (DM) and hypertension (HTN) have been on the rise in recent decades all over the world more remarkably in developing countries like India. We intend to measure the prevalence of DM and HTN in the Indian population and to compare the trends and various correlates of these diseases in NFHS (National Family Health Survey)-4 and 5. Data of NFHS-4 and 5 were accessed from dhs program website. All statistical analyses were done in SAS (version 9.4). Mixed effects survey logistic regression models were used for estimating odds ratio (OR).p-values <0.05 were considered significant .1,637,762 individual case entries were evaluated. Both the diseases showed an increasing trend as per the advancing age in both sexes. The highest prevalence of DM is seen in the age group of 45-49 years (7.8%) in females and > 50 years (11.9%) in males as per NFHS-5. Similarly, the highest prevalence of HTN was seen in the age group of45-49 years (31.2%) in females and > 50 years (41.4%) in males as per NFHS-5. The OR (95% CI) of prevalence of DM, HTN and both the diseases in age group >50 years was 14.46 (13.14-15.7), 16.65 (15.78-17.6), 79.5 (64.76-97.73) respectively when compared to reference age group15-19 years. Highest odds for having both DM, HTN concurrently was in age >50 years with aOR(95% CI) 65.32 (52.26-72.63) in NFHS 4 and 35.57 (97.47-45.53) in NFHS 5.Rise in prevalence of DM, HTN and concurrent presence is noted with an apparent increase in cases.

Impact of Lockdown on Air Quality in the Most Polluted Cities of India.

Background: COVID-19 has become a global pandemic, prompting lockdowns in practically every country. To prevent the spread of the disease, India has enforced a rigorous nationwide lockdown that commenced in March 2020. The lockdown imposed amid the pandemic ensured that most commercial activities and vehicle transportation ceased, resulting in a significant reduction in air pollution levels. Material and Methods: The value of air pollutants PM10, PM2.5, NO2, and SO2 from January to May 2020 was obtained from the Indian Central Pollution Control Board. Before lockdown and during lockdown, relative fluctuations in ambient concentrations of four air contaminants were investigated. The Box-Jenkins approach was used to estimate future air pollution data points using time series data analysis. Results: The PM10 level reduced by 61%, 30%, 68%, 37%, and 43% in the selected cities, respectively. Comparison of other pollutant concentrations before and after the lockdown also found a reduction in ambient pollutant concentrations, resulting in improved air quality. Inference of predicted model values to observed values revealed a significant increase in the concentrations of all pollutants. The percentage increases in AQImean from predicted to observed values were 206% in Ghaziabad, 148% in Delhi, 59% in Hyderabad, and 160% in Cochin. Conclusion: The strict lockdown has resulted in a significant drop in air pollutant levels. Upgrading present technologies could help keep pollution to a minimum of 37% under control. The findings would prompt the government to consider how to strictly reduce vehicle and industrial pollution to improve air quality and maintain improved public health.

Waning of Antibody Response Among Vaccinees who Received Two Doses of Covishield Vaccine.

Introduction: There are limited data available on the long-term presence of SARS-CoV-2-specific binding antibodies and neutralizing antibodies in circulation among the elderly population. This study aims to examine levels of anti-SARS-CoV-2 antibodies in vaccines who have completed at least 6 months since the second vaccine dose. A cross-sectional study was conducted from November 2021 to January 2022 among 199 vaccines aged 60 years and above residing in Belagavi city, who received two doses of the Covishield vaccine. Methods: Antibody response to SARS-COV-2 virus whole cell antigen was measured by a kit COVID KAWACH IgG Micro LISA (J Mitra and Company, India) in 199 participants who had completed at least 6 months after receiving the second dose of Covishield vaccine. The antibody response was measured as a ratio of optical density (OD) in the participant's sample to the mean OD in negative control test by normal (T/N). Independent Kruskal-Wallis test was applied to test the difference between the T/N ratio by months of vaccination since the second dose and by the age group strata. Results: The median T/N values among participants who completed 6, 7, 8, and 9 months since the second vaccine dose were 14.17, 10.46, 7.93, and 5.11, respectively, and this decline in T/N values was statistically significant. Antibody response values showed a decline with increasing age for participants in the age strata 60-69, 70-79, and 80 and above, respectively. Conclusions: A significant decline was observed in antibody response over 9 months supporting the administration of booster dose of vaccine.

Low Birth Weight, the Differentiating Risk Factor for Stunting among Preschool Children in India.

Background: The prevalence of low birth weight (LBW) is a major public health issue in India; however, the optimal growth pattern for such infants is not clear. The purpose of this study is to understand the causal association between LBW and stunting of preschool children in India. Methods: The National Family Health Survey-4 is a large cross-sectional survey based on a nationally representative sample of 699,686 women in the age group of 15−49 years and was conducted during 2015−2016 in India. The study used the children's file with a sample of 259,002 of 0−59 months for investigation. Results: The data revealed that 38.7% of the children in India were stunted. The bivariate analysis revealed that, of the women who did not attend any antenatal care (ANC) meetings, 46.8% had stunted children compared to the women who attended more than three ANC meetings, which 30.7% had stunted children. The low birth weight children experienced a much higher chance of stunting compared to children with a normal birth weight (44.3% vs. 33.8%). The multivariable odds ratios of logistic regression, after adjusting for the confounding characteristics, showed that pregnant women attending more than three ANC meetings compared to not attending any ANC meetings experienced a 19% lower adjusted odds ratio (AOR) of having stunted children (AOR = 0.81; CI 0.78, 0.85; p < 0.001). Another important variable, such as women with underweight body mass index (BMI) compared with normal BMI, had 6% higher odds of having stunted children (AOR = 1.06; CI 1.03, 1.10; p < 0.001). Similarly, women who belong to the Scheduled Caste compared to the General Caste had 36% higher odds of having stunted children (AOR = 1.36; CI 1.30, 1.42; p < 0.001); and children aged 13−23 months compared to children up to one-year-old or younger had 141% higher odds of being stunted (AOR = 2.41; CI 2.32, 2.51; p < 0.001). The conspicuous finding is that LBW babies, after adjusting for other important confounding factors, such as BMI and ANC, experienced 19% higher odds of stunted children (AOR = 1.19; CI 1.14, 1.24; p < 0.001) compared to normal birth weight babies. Conclusions: The results revealed LBW is associated with stunting of preschool children in India.

Growth Estimation of Under-Five Children Using Statistical Models in Central Region of India.

BACKGROUND AND AIMS: To determine the suitability of 11 basic statistical models for estimating child-growth of under-five children and to bring-forth estimated growth curves for mean height & mean weight by their selected birth-weight categories for Central Region of India. METHODS: The study used fourth round of National Family Health Survey-4 (NFHS-4) data of India, consisting of 75,645 under-five children, belonging to 3 Indian States - Chhattisgarh, Madhya Pradesh & Uttar Pradesh. The children of the Region were first divided into 4 sub categories according to their birth-weight: (i) < 2000 gm, (ii) 2000-2499 gm, (iii) 2500-2999 gm (iv) 3000+gm, growth curve for mean height and mean weight were estimated for two sexes. RESULTS: The significant association of 7 socio-demographic factors studied, namely - age & sex of child, birth-order, BMI, mother's highest level of education, place of residence and wealth index. Further, Cubic Model and Power Model, demonstrated best-fit to height & weight data of under-five children, belonging to different birth-weight categories, for estimating growth of boys & girls separately. These models enabled us to estimate mean height and mean weight, with 95% CI, for boys and girls separately by different birth-weight categories. CONCLUSIONS: Study concluded that 7 socio-demographic factors were significantly associated with birth-weight. Further, Cubic Model and Power Model were most suitable for estimating child growth in terms of mean height & mean weight for boys and girls - considering specific birth-weight categories.

Liver profile in COVID-19: a meta-analysis.

BACKGROUND: Few studies have been performed to investigate multiorgan failure occurring with extrapulmonary symptoms like diarrhea, anorexia, and vomiting. There has been no attempt at a systematic review on this major health issue. Hence, in this study, a meta-analysis was undertaken to quantify the overall risk of liver damage in COVID-19 patients and also find the overall variation in risk outcome. MATERIALS AND METHODS: A meta-analysis was carried out on the findings of four published studies that were related to the albumin, alanine aminotransferase (ALT), and aspartate aminotransferase (AST) levels of COVID-19 patients. The pooled mean for each of these three measurements was estimated by using a random-effects model. RESULTS: The pooled means for albumin, AST, and ALT in COVID-19 patients were 38.84 g/L [95% confidence interval (CI): 35.83-41.86], 27.28 IU/L (95% CI: 18.30-36.26), and 24.44 IU/L (95% CI: 15.73-33.15) respectively. There was a high degree of divergence among the studies, with the index of heterogeneity being more than 90%. CONCLUSION: The ALT and albumin pooled means were reported to be within the normal range; however, the pooled mean of the serum AST level was found to be high in COVID-19 patients. The pooled means reported in this study can be useful for working out the degree of liver damage in COVID-19 patients.

Growth Prediction of Under-5 Children Using Statistical Models for Eastern Region of India.

Background: Percentile curves are often used to assess variances in children's growth pattern. This study is aimed at explaining effect of the respondents' sociodemographic characteristics on under-5 children's birth weight and identifying most suitable models, out of 11 statistical models reviewed, for estimating children's growth in terms of height and weight of a given birth-weight category and obtain estimated growth curves. Material and Methods: The study used National Family Health Survey (NFHS)-4 data from four Eastern States of India, consisting of 54,075 under-5 children. Estimated growth curves were obtained, using best-fit models. Results: Birth weight was found to be associated with children's age, gender, birth order, body mass index, mother's education, living place and wealth index. Two models - Cubic Model and Power Model - showed best fit to the height and weight measurements. We obtained estimated growth curves of boys and girls for a given birth-weight category. Conclusions: All socio-demographic factors studied, except respondent's occupation, were associated with children's birth weight. Cubic and Power Models were most suitable for assessing growth in terms of height and weight of boys and girls, belonging to a given birth-weight category.

Statistical Model for COVID-19 in Different Waves of South Indian States.

Background: COVID-19 has resurfaced in India, where it is rapidly spreading and wreaking havoc in rural areas. An effort has been undertaken to assess the levels and patterns of COVID-19 active cases in the southern states of India. To trace and reason out anomalous trends in the COVID-19 curve so that particular actions such as lockdown, de-lockdown, and healthcare improvisation can be implemented at the appropriate time. Methods: The data has retrieved from the government websites through a platform called Kaggle. The entire duration of COVID - 19 were classified into three compartments: Phase one, Resting phase, and Phase two. The Case Fatality Rate in south Indian states was analysed corresponding to the phases, and a compartmental model for COVID-19 dynamics in the region was proposed. Results: The quadratic regression model was fitted and found to be the best model for the phases except for the resting phase. Phase one was comparatively less fitted when compared to phase two. In most of the south Indian states, the active cases in phase one were almost more than four times that of phase two. The average CFR value in phase one was lower than the subsequent phase in all of the southern Indian states. In phase one, Telangana, Karnataka, and Tamil Nadu had the highest CFR (4.77,4.22, and 3.71, respectively), whereas Lakshadweep and Kerala had the lowest CFR (0.27 and 0.71, respectively). In the resting phase, the CFR stabilized in all states and reached a value between 0.2 to 2. The trend was similar in phase two also, CFR of Lakshadweep, Kerala, Telangana, and Andhra Pradesh (0.143, 0.416,0.553, 0.803) were very low, while the CFR of Andaman and Nicobar Islands, Karnataka, and Tamil Nadu (1.237, 1.306, 1.490) were very high. Conclusion: The first and second phases of the COVID-19 virus in south Indian states had different characteristics. A District-level working group with the autonomy to respond to rapidly changing local situations must be empowered to tackle the next phase. The upcoming phases could be more peaked in less time and could be a hectic situation for the health care system.

Effect of wealth, social inequality, Mother's BMI, and education level on child malnutrition in India.

BACKGROUND AND AIMS: The differences in prevalence of malnutrition are mostly on account of social factors. However, we did not find any published study that provided an estimate of proportion of stunting and underweight among under-5 children due to household economic conditions, social inequalities, mother's BMI and education level. Hence, study has taken to study the effect of household economic status, social inequality, mother's BMI and education on stunting and underweight among children under-5 years and its determinants. METHODS: The study used Kids file of NFHS-4 (2015-16), which comprised 259,627 children aged less than five years. This data was analysed by bivariate and Forward Logistic Regression techniques using M.S. Excel and IBM SPSS-22 version. RESULTS: The prevalence of stunting and underweight children was significantly higher among those born to underweight mothers, poor households, working women, and women had a home delivery. It was also high among children of 4th or higher birth order, those from scheduled castes and tribes, born to illiterate women and those residing in rural. The odds of stunting (OR = 2.67, 95% CI: 2.54-2.81) and underweight (OR = 2.74, 95% CI: 2.60-2.88) were more than two times higher among children living in poor households than among those from rich households. Poor households account for about 40% of stunted and underweight children. Fifteen percent of stunted children and 26.9% of underweight were born to underweight mothers. Overall, 60% of stunted and 56.6% of underweight children had illiterate mothers. CONCLUSIONS: children of illiterate and underweight mothers, socially deprived and economically poor groups are at a higher risk of being stunted and underweight. Hence, necessary health programmes are needed for improving nutritional status by giving special attention to illiterate, underweight mothers, socially deprived and economically poor groups.

Stunting, wasting and underweight as indicators of under-nutrition in under five children from developing Countries: A systematic review.

BACKGROUND AND AIMS: To compute reliable estimates of stunting, wasting and underweight along with their determinants in under 5 children from Developing Countries. METHODS: Out of 190 studies on under-nutrition, accessed from PubMed and Google database, 24 studies meeting the selection criteria were considered for meta-analysis. RESULTS: Overall estimate of prevalence of stunting, wasting and underweight were 43.4%, 17.8% and 35.5% respectively. Mother's education, BMI, height, wealth index, child birth-weight and sex were factors significantly associated with stunting, wasting and underweight. CONCLUSIONS: Prevalence of stunting, wasting and underweight in Developing Countries were quite high. To carry-out differentials of under-nutrition between countries and ways of its reduction, more such studies are required.

Risk factors of diabetes and hypertension among women in Karnataka.

BACKGROUND AND AIMS: The growth in prevalence of diabetes and hypertension has become a major health issue for women in Karnataka. In India, for the first time, the National Family Health Survey has collected information on diabetes and hypertension across the states within India (NFHS-4, 2015-16). Hence there is the need to estimate the prevalence of diabetes and hypertension among women and the associated risk factors using the national represented data. METHODS: This study has used data from the fourth round of the National Family Health Survey, which was conducted in 2015-16. Furthermore, the present study included 26,291 women of Karnataka aged 15-49 years. And data analysis was carried out by univariate, bivariate and Binary Logistic Regression techniques. RESULTS: This study revealed a high prevalence of diabetes (6.3%) and hypertension (10.5%) among women in Karnataka. Overweight women were more likely to have diabetes (11.7%) and hypertension (20.6%) than normal and underweight women. The detailed analysis indicated demographic and socio-economic diversity in the burden of diabetes and hypertension. The factors responsible for co-morbidities were the changes in the demographic situation and socio-economic status, overweight and substance use. CONCLUSIONS: The findings point to the need for raising awareness about the prevention and management of diabetes and hypertension through health education and community-based disease management programs with the help of trained peers and community health workers.

Burden of increased blood glucose due to modifiable risk factors among men in India.

BACKGROUND AND AIMS: Worldwide, many diabetes cases are occurring mainly due to lifestyle risk factors. Hence, to quantify and compare the attributable burden of key modifiable risk factors associated with increased Blood Glucose (BG) among Indian states and districts. METHODS: The study used the National Family Health Survey (2015-16) data to estimate Population Attributable Risk (PAR) for increased BG (>140 mg/dl) among men aged 15-54 years in 640 districts of 36 States/Union Territories (UTs), India. We have considered three key modifiable factors such as high Body Mass Index (BMI), use of tobacco and alcohol. Population Attributable Risk techniques were employed to address the attributable burden of increased blood glucose due to modifiable risk factors. RESULTS: Substantial variations were found in the burden of increased BG due to high BMI, alcohol and tobacco use in India. The overall burden of increased BG due to high BMI, tobacco and alcohol in India was 28.5%, 2.1% and 6.4%, respectively. Regional variations in BG were found in high BMI, tobacco and alcohol consumption groups. The high burden of increased BG related to the above key modifiable risk factors mostly seen in North-Eastern' districts due to alcohol, Southern and Northern' districts was due to high BMI. However, the higher burden due to tobacco was reported in Central, Eastern and North-Eastern' districts. CONCLUSION: Three modifiable risk factors are contributing significantly to increased BG among men. Since there are regional differences in their contributions, state/district, specific targeted interventions may be necessary to control increased BG among men in India.

COVID-19 pandemic and its average recovery time in Indian states.

BACKGROUND: Many studies have been carried out in modelling COVID-19 pandemic. However, region-wise average duration of recovery from COVID-19 has not been attempted; hence, an effort has been made to estimate state-wise recovery duration of India's COVID-19 patients. Determining the recovery time in each region is intended to assist healthcare professionals in providing better care and planning of logistics. METHODS: This study used database provided by Kaggle, which takes data from the Ministry of Health & Family Welfare. The simple Linear Regression model between incidence, prevalence, and duration was used to assess the duration of COVID-19 disease in various Indian states. RESULTS: The fitted model suits ideal for most of the states, except for some union territories and northeastern states. The average time to recover from disease was ranging from 5 to 36 days in Indian states/union territories except for Madhya Pradesh. Tamil Nadu has an average recovery time of 7 days with an value of 0.96, followed by Odisha, Karnataka, West Bengal, Kerala and Chhattisgarh and the average recovery duration was estimated as 7, 13, 17, 11, 14 and 12 days respectively. CONCLUSION: The average recovery from COVID-19 was ten or less days in twenty percentage of states, whereas in forty-four percentage of states/union territories had an average recovery duration between ten to twenty days. However, around twentyfour percentage of states/union territory recovered between twenty to thirty days. In the rest of Indian states/union territories, the average duration of recovery was more than thirty days.

Age at menopause in India: A systematic review.

BACKGROUND AND AIMS: Menopause is a physiological process in nature and hence, variations in the age of menopause are not expected. Hence, the study was conducted with an objective to calculate the reliable estimates of age at menopause for India, and understand the differentials in women's age at menopause throughout the country. METHODS: A total of 202 studies of age at menopause, covering the period 2009-2020, were accessed from PubMed database and Google. Of these only ten studies met the selection criteria for this paper, which is that the data for these studies must be collected from house-to-house surveys. RESULTS: The average age at menopause in India, with minimal publication bias, is 46.6 years (95% CI: 44.83, 48.44). In one study slightly above 1.96 Standard Deviation, was observed, as ascertained by Funnel Plot and Egger's test. The mean age ranged from a minimum of 44.69 years (95% CI: 35.01, 54.37) to a maximum of 48.95 (95% CI: 42.29, 55.61) years. Furthermore, the age at menopause did not exhibit any significant variation by age at menarche, although the association was positive. CONCLUSIONS: The age at menopause showed positive association with age at menarche. In India, during the period 2009-2020, it was 46.6 years, which significantly lower than the age in some developed countries. The differences may be methodological since no information was found regarding the distribution of age at menopause in the studies that were considered for meta-analysis.

Trends in and determinants of neonatal and infant mortality in Nigeria based on Demographic and Health Survey data.

This study aimed to assess the changes in neonatal and infant mortality rates in Nigeria over the period 1990 to 2018 using Nigerian Demographic and Health Survey (NDHS) data, and assess their socio-demographic determinants using data from the most recent survey conducted in 2018. The infant mortality rate was 87 per 1000 live births in 1990, and this increased to 100 per 1000 live births in 2003 - an increase of around 15% over 13 years. Neonatal and infant mortality rates started to decline steadily thereafter and continued to do so until 2013. After 2013, neonatal morality rose slightly by the year 2018. Information for 27,465 infants under 1 year of age from the NDHS-2018 was analysed using bivariate and multivariate analysis and the Cox proportional hazard technique. In 2018, infant deaths decreased as wealth increased, and the incidence of infant deaths was greater among those of Islam religion than among those of other religions. A negative association was found between infant deaths and the size of a child at birth. Infant mortality was higher in rural than in urban areas, and was higher among male than female children. Both neonatal and infant death rates varied by region and were found to be highest in the North West region and lowest in the South region. An increasing trend was observed in neonatal mortality in the 5-year period from 2013 to 2018. Policy interventions should be focused on the poor classes, women with a birth interval of less than 2 years and those living in the North West region of the country.

Increased blood glucose level following hysterectomy among reproductive women in India.

BACKGROUND: In recent years, the hysterectomy, a surgical removal of the uterus, has received increased attention in health policy debates in India. The trigger for this was a series of media reports that highlighted an unusual surge in the number of women undergoing hysterectomies with a significant number of cases involving young and early menopausal women from low-income families. When menopause occurs as a result of hysterectomy, then the hormones such as estrogen and progesterone affect how the body cells respond to insulin. To date, we have not come across a national study following blood glucose levels among women who undergo a hysterectomy. METHODS: The study used the Indian fourth round of National Family Health Survey data, which is a cross-sectional nationally representative sample of 699,686 women in the age group 15-49 years and conducted during 2015-16. Bivariate and multivariate logistic regressions were used to examine the effect of hysterectomy on blood glucose level of > 140 mg/dl among women of reproductive age groups. RESULTS: The blood glucose level of > 140 mg/dl was much higher among women who had undergone a hysterectomy (12.2%) compared to non-hysterectomy women (5.7%). The pattern holds true among relevant background characteristics such as age, place of residence, education, caste, religion, wealth, marital status, body mass index (BMI), anaemia and consumption of tobacco. The adjusted odds after controlling for significant background factors, women who underwent hysterectomy experienced 15% higher odds of blood glucose level of > 140 mg/dl compared those who did not. CONCLUSIONS: The results indicated increased blood glucose level among women post hysterectomy. Hence, the government of India should consider developing evidence-based policies and programming to provide effective targeted interventions for the better reproductive health of women.