Prevalence and detecting spatial clustering of diabetes at the district level in India

Spatial Clustering of Malnutrition and Anemia Among Reproductive Women and Its Associated Risk Factors in India: Evidence From National Family Health Survey-5

BACKGROUND

Malnutrition and anemia are 2 severe public health concerns, predominantly in low-and middle-income nations. Malnutrition is defined as poor nutritional condition that encompasses both under nutrition and over nutrition. The prevalence of overweight or obesity and anemia has increased in India from 2016 to 2021. The study aims to investigate the spatial clustering and factors responsible for underweight, overweight/obesity, and anemia among reproductive women (15-49 years) in India using the data from National Family and Health Survey-5 (2019-2021).

METHODS

We conducted hot-spot analysis using Moran's Index (MI) with the help of spatial analysis software (i.e., GeoDa 1.18 and ArcGIS 10.8). It also demonstrates the autocorrelation. Multivariable logistic regression analysis has been performed to examine different determinants and risk associated with underweight, overweight/obesity, and anemia with various dependent variable by using Stata-14 software.

RESULTS

Moran's Index for underweight (MI = 0.68), overweight/obesity (MI = 0.72), and anemia (MI = 0.62) indicates a high level of spatial-autocorrelation (P < .001) exists across the districts in India. As a result, a total of 156, 143, and 126 hot-spot districts are detected for underweight, overweight/obesity, and anemia, respectively. The burden of undernutrition and anemia is higher in rural areas. Risk of under nutrition and anemia are both reduced by media exposure and eating habits. Moreover, low income and low education level raises the risk of anemia and undernutrition, while obesity shows an inverse trend with income and education level.

CONCLUSION

The study recommends targeting hot-spot districts for malnutrition and anemia, and policy level initiatives by addressing the responsible risk factors.

Status and correlates of non-communicable diseases among children and adolescents in slum and non-slum areas of India's four metropolitan cities

The emergence of non-communicable diseases (NCDs) in childhood poses a serious risk to a healthy adult life. The present study aimed to estimate the prevalence of NCDs among children and adolescents in slums and non-slums areas of four metropolitan cities of India, and in rural areas of the respective states The study further, investigated the effect of the place residence as slum vs. non-slum and other risk factors of the NCDs. Nationally representative data from the Comprehensive National Nutrition Survey (CNNS) was used.. Estimates were based on children (5-9 years) and adolescents (10-19 years) for whom biomarkers predicting diabetes, high total cholesterol, high triglycerides and hypertension were determined. Weight, height and age data were used to calculate z-scores of the body mass index. Overweight and obesity was higher in urban areas than in rural areas among children and adolescents. Regional differences in the prevalence of diseases were observed; children in Delhi and Chennai had a higher likelihood of being diabetic while children in Kolkata were at a greater risk of high total cholesterol and high triglycerides. The risk of hypertension was strikingly high among non-slum children in Delhi. Children from slums were at a higher risk of diabetes compared to the children from non-slums, while children and adolecents from non-slums were at a greater risk of high triglycerides and hypertension respectively than their counterparts from slums. Male children and adolecents had a higher risk of diabetes and high cholesterol. Screening of children for early detection of NCDs should be integrated with the already existing child and adolescent development schemes in schools and the community can help in prevention and control of NCDs in childhood.

Identifying spatial clustering of diarrhoea among children under 5 years across 707 districts in India: a cross sectional study

BACKGROUND

Diarrhoea is one of the leading reasons for under-five child mortality and morbidity across the globe and especially in low- and middle-income countries like India. The present study aims to investigate and identify the spatial clustering and the factors associated with diarrhoea across 707 districts of different states in India.

METHODS

This study used National Family Health Survey-4 & 5 (2015-16 & 2019-21) data in India. Spatial analysis software i.e., ArcGIS and GeoDa including Moran's statistics have been applied to detect the spatial prevalence and auto-correlation of diarrhoea among neighbourhood districts. Bivariate analysis with a chi-square test and logistic regression has been performed to identify the factors associated with the morbidity condition.

RESULTS

The result shows out of 2,23,785 children, 7.3 percent children suffer from diarrhoea in India. The prevalence is highest in Bihar (13.7%) and lowest in Lakshadweep (2.3%). Around 33 percent of districts have reported more than the national average level of diarrhoea prevalence. The study also found a medium to high level of autocorrelation with 0.41 Moran's Index value and detected 69 hot-spots districts mostly from Maharashtra, Bihar, Odisha, and Gujarat. The study has also found, with an increase in children's age as well as mother's age the prevalence of the disease decreases. The prevalence is more among male children than females. Underweight [OR = 1.08, 95% CI (1.03-1.13)] children have a greater risk of suffering from diarrhoeal diseases. The odds of children living in a pucca house [OR = 0.89, 95% CI (0.68-1.16)] are less likely to suffer from diarrhoea. On the other hand, rich economic status [OR = 0.91, 95% CI (0.86-0.97)], reduce the risk of such morbid conditions.

CONCLUSION

The study recommends targeting the hot-spot districts with high prevalence areas, and district-level interventions by improving housing type and child nutrition status, which can help to prevent diarrhoeal diseases among children in India. Thus, the identification of hotspot districts and suggested policy interventions by the current study can help to prevent childhood mortality and morbidity, as well as to achieve the target given by Sustainable development Goals 3.2.

Spatial Patterns and Determinants of Diabetes Mellitus in Indian Adult Population: a Secondary Data Analysis from Nationally Representative Surveys

INTRODUCTION

Diabetes mellitus (DM) is a major public health challenge around the world. It is crucial to understand the geographic distribution of the disease in order to pinpoint high-priority locations and focus intervention on the target populations. Hence, this study was carried out to determine the spatial pattern and determinants of type-2 DM in an Indian population using National Family Health Survey-4 (NFHS-4) and Longitudinal Aging Survey in India (LASI).

METHODS

We have adopted an ecological approach, wherein geospatial analysis was performed using aggregated district-level data from NFHS-4 (613 districts) and LASI survey datasets (632 districts). Moran's I statistic was determined and Local Indicators of Spatial Association (LISA) maps were created to understand the spatial clustering pattern of DM. Spatial regression models were run to determine the spatial factors associated with DM.

RESULTS

Prevalence of self-reported DM among males (15-50 years) and females (15-49 years) was 2.1% [95% confidence interval (CI) 2.0-2.3%] and 1.7% (95% CI 1.6-1.8%), respectively. Prevalence of self-reported DM among males and females aged 45 years and above was 12.5% (95% CI 11.5-13.5%) and 10.9% (95% CI 9.8-12%). Positive spatial autocorrelation with significant Moran's I was found for both males and females in both NFHS-4 and LASI data. High-prevalence clustering (hotspots) was maximum among the districts belonging to southern states such as Kerala, Tamil Nadu, Karnataka, and Andhra Pradesh. Northern and central states like Madhya Pradesh, Chhattisgarh, and Haryana mostly had clustering of cold spots (i.e., lower prevalence clustered in the neighboring regions).

CONCLUSION

DM burden in India is spatially clustered. Southern states had the highest level of spatial clustering. Targeted interventions with intersectoral coordination are necessary across the geographically clustered hotspots of DM.

Dietary diversity and association with non-communicable diseases (NCDs) among adult men (15-54 years): A cross-sectional study using National Family and Health Survey, India

A healthy and diversified diet is essential for preventing several non-communicable diseases (NCDs). Given the increasing evidence of diet-related health burdens and the rising prevalence of NCDs among Indian adults, the present study aims to explore dietary diversity patterns among adult men in India and their association with non-communicable diseases (NCDs). For this purpose, the study used the fourth round of the National Family and Health Survey (NFHS-4) to analyze adult male samples (n = 1,12,122). Dietary Diversity Scores (DDS) were computed by the weighted sum of the number of different food groups consumed by an individual. The prevalence of diabetes, heart disease, and cancer among adult men is considered a non-communicable disease. Bivariate and logistic regression was carried out to examine the association between DDS and NCDs by estimating chi-squared tests (χ2-test), odds ratio (OR), and 95% confidence interval (CI). The prevalence of diabetes, heart disease, and cancer among adult men in India is 2.1 percent, 1.2 percent, and 0.3 percent, respectively. Results show a positive association between dietary diversity score and the prevalence of the non-communicable disease. High-level dietary diversity scores increase to two times the likelihood of diabetes (OR 2.15 with p<0.05) among adult men than to better-off counterparts while controlling all the covariates. However, a moderate dietary diversity score significantly decreases the likelihood of heart disease (OR 0.88 with p<0.10) and Cancer (OR 0.71 with p<0.05) for adult men compared to a lower score of dietary diversity. In addition, age, marital status, drinking and smoking habits, occupation, and wealth index are also significantly associated with the odds of non-communicable diseases among adult men.

Challenges of diabetes care in India: Results from a Family Cohort Study

OBJECTIVES

Diabetes is a significant public health concern in India, with Kerala being labeled as the diabetes capital of the country. The study aims to evaluate the prevalence, treatment, and management of diabetes to examine the unmet need for care to propose cost-effective strategies.

DESIGN

A cross-sectional study was conducted on a geographically defined cohort population in Ernakulam.

SAMPLE

This paper presents diabetes data of adults ≥30 years enrolled from the community cohort. The interviews were conducted with 997 participants at their residence.

MEASUREMENT

Random blood glucose was assessed for each participant using a finger prick test.

RESULTS

The overall prevalence of diabetes was 30.1%, of which 4.1% of participants had undiagnosed diabetes. Among those with diabetes, 86.3% were aware of their diagnosis; among those aware, 86.5% were on treatment. Among those on treatment for diabetes, 54% achieved controlled blood sugar.

CONCLUSION

The challenge in diabetes management is controlling the blood glucose levels of people who adhere to treatment. Younger employed females from lower-income quartiles have the highest risk. The study also raises questions about quality and strategies for medication compliance. The findings inspire future research on care needs, policies, and program responses to reduce the diabetes disease burden.

Spatiotemporal Analysis and Risk Assessment Model Research of Diabetes among People over 45 Years Old in China

Diabetes, which is a chronic disease with a high prevalence in people over 45 years old in China, is a public health issue of global concern. In order to explore the spatiotemporal patterns of diabetes among people over 45 years old in China, to find out diabetes risk factors, and to assess its risk, we used spatial autocorrelation, spatiotemporal cluster analysis, binary logistic regression, and a random forest model in this study. The results of the spatial autocorrelation analysis and the spatiotemporal clustering analysis showed that diabetes patients are mainly clustered near the Beijing−Tianjin−Hebei region, and that the prevalence of diabetes clusters is waning. Age, hypertension, dyslipidemia, and smoking history were all diabetes risk factors (p < 0.05), but the spatial heterogeneity of these factors was weak. Compared with the binary logistic regression model, the random forest model showed better accuracy in assessing diabetes risk. According to the assessment risk map generated by the random forest model, the northeast region and the Beijing−Tianjin−Hebei region are high-risk areas for diabetes.

A structured additive modeling of diabetes and hypertension in Northeast India

Background

Multiple factors are associated with the risk of diabetes and hypertension. In India, they vary widely even from one district to another. Therefore, strategies for controlling diabetes and hypertension should appropriately address local risk factors and take into account the specific causes of the prevalence of diabetes and hypertension at sub-population levels and in specific settings. This paper examines the demographic and socioeconomic risk factors as well as the spatial disparity of diabetes and hypertension among adults aged 15–49 years in Northeast India.

Methods

The study used data from the Indian Demographic Health Survey, which was conducted across the country between 2015 and 2016. All men and women between the ages of 15 and 49 years were tested for diabetes and hypertension as part of the survey. A Bayesian geo-additive model was used to determine the risk factors of diabetes and hypertension.

Results

The prevalence rates of diabetes and hypertension in Northeast India were, respectively, 6.38% and 16.21%. The prevalence was higher among males, urban residents, and those who were widowed/divorced/separated. The functional relationship between household wealth index and diabetes and hypertension was found to be an inverted U-shape. As the household wealth status increased, its effect on diabetes also increased. However, interestingly, the inverse was observed in the case of hypertension, that is, as the household wealth status increased, its effect on hypertension decreased. The unstructured spatial variation in diabetes was mainly due to the unobserved risk factors present within a district that were not related to the nearby districts, while for hypertension, the structured spatial variation was due to the unobserved factors that were related to the nearby districts.

Conclusion

Diabetes and hypertension control measures should consider both local and non-local factors that contribute to the spatial heterogeneity. More importance should be given to efforts aimed at evaluating district-specific factors in the prevalence of diabetes within a region.

Prevalence and factors associated with diabetes mellitus among tuberculosis patients in South India-a cross-sectional analytical study

OBJECTIVE

To determine the prevalence and determinants of diabetes mellitus (DM) among tuberculosis (TB) patients and to assess the additional yield and number needed to screen (NNS) to obtain a newly diagnosed DM among TB patients.

DESIGN

We undertook a cross-sectional analysis of the cohort data under Regional Prospective Observational Research for Tuberculosis-India consortium. Newly diagnosed TB patients recruited into the cohort between 2014 and 2018 were included. Pretested standardised questionnaires and tools were used for data collection. Prevalence of DM among TB patients was summarised as proportion with 95% CI. Type II DM was diagnosed if random blood sugar level was >200 mg/dL or if the participant had a documented history of DM. NNS by blood glucose testing to diagnose one new DM case among TB patients was also calculated.

SETTING

Three districts of South India: Puducherry, Cuddalore and Villupuram SUBJECTS: Newly diagnosed sputum smear positive pulmonary TB patients aged ≥16 years RESULTS: In total, 1188 TB patients were included. Prevalence of DM among TB patients was 39% (95% CI: 36.2% to 41.8%). In unadjusted analysis, elderly TB, marital status, caste, gender, higher education level, household income and obesity had a significant association with DM. However, in adjusted analysis, only marital status (currently married aPR; 3.77 (95 CI: 2.20 to 6.49), widowed/separated/divorced aPR; 3.66 (95 CI: 1.96 to 6.83)) and body mass index category (normal weight aPR; 3.26 (95 CI: 2.55 to 4.16), overweight aPR; 3.86 (95 CI: 2.69 to 5.52), obesity aPR; 4.08 (95 CI: 2.81 to 5.94)) were found to be significant determinants. The number of TB patients needed to be screened to find a new DM case was 12.

CONCLUSION

We found that one in three TB patients had coexisting DM. The number of TB patients needed to be screened to obtain a newly diagnosed DM patients was also determined. The study supports and highlights the need of RNTCP's effort in bidirectional screening of TB and DM.