Dataset Information

Prevalence of Gestational Diabetes in India by Individual Socioeconomic, Demographic, and Clinical Factors.

ABSTRACT: Importance:Gestational diabetes is common in pregnancy and is associated with adverse pregnancy and fetal outcomes. Currently, population-based data on the prevalence of gestational diabetes are limited in India. Objective:To provide a comprehensive national assessment of gestational diabetes in India and its socioeconomic, demographic, and geographic associations, using elevated random blood glucose data as a proxy for a gestational diabetes diagnosis. Design, Setting, and Participants:This cross-sectional study analyzed the fourth National Family Health Survey, conducted in India between January 2015 and December 2016. This nationally representative sample comprised 699?686 women 15 to 49 years of age, of whom 32?428 (4.6%) were pregnant. Data were analyzed between July and December 2019 and between July and August 2020. Exposures:Age, body mass index, hypertension, wealth, and social caste were factors potentially associated with gestational diabetes. Main Outcomes and Measures:Gestational diabetes, defined as elevated random blood glucose according to predetermined thresholds (?200 mg/dL for nonfasting, ?92 mg/dL for fasting). Results:Of the 31?746 pregnant women with complete data in the study, the mean (SD) age was 24.3 (4.7) years, and the mean (SD) gestational age was 5.1 (2.3) months. The weighted age-adjusted prevalence of gestational diabetes was 1.3% (95% CI, 1.1%-1.5%). The prevalence of gestational diabetes increased with age, from 1.0% (95% CI, 0.5%-1.5%) at age 15 to 19 years to 2.4% (95% CI, 1.0%-3.8%) at age 35 years or older. The age-adjusted prevalence of gestational diabetes was higher among women with a body mass index of 27.5 or greater (1.8%; 95% CI, 1.0%-2.5%) compared with women with a body mass index of less than 18.5 (0.8%; 95% CI, 0.5%-1.1%), among women in the highest wealth quartile (1.7%; 95% CI, 1.1%-2.5%) compared with those in the lowest (0.9%; 95% CI, 0.7%-1.2%), and women in the south (eg, Kerala: 4.5%; 95% CI, 2.4%-6.7%; Telangana: 5.4%; 95% CI, 0.0%-11.0%) compared with the northeast (eg, Assam: 0.23%; 95% CI, 0.0%-0.48%; Mizoram: 0.16%; 95% CI, 0.0%-0.49%). Conclusions and Relevance:In this study, considerable variation was found in the prevalence of gestational diabetes by state, socioeconomic status, and demographic factors. This finding has implications for the method of gestational diabetes screening in low-resource settings in India, especially in areas or among demographic groups with lower prevalence.

SUBMITTER: Swaminathan G

PROVIDER: S-EPMC7653498 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Prevalence of Gestational Diabetes in India by Individual Socioeconomic, Demographic, and Clinical Factors.

Swaminathan Goutham G Swaminathan Akshay A Corsi Daniel J DJ

JAMA network open 20201102 11

<h4>Importance</h4>Gestational diabetes is common in pregnancy and is associated with adverse pregnancy and fetal outcomes. Currently, population-based data on the prevalence of gestational diabetes are limited in India.<h4>Objective</h4>To provide a comprehensive national assessment of gestational diabetes in India and its socioeconomic, demographic, and geographic associations, using elevated random blood glucose data as a proxy for a gestational diabetes diagnosis.<h4>Design, setting, and par ...[more]

PMID: 33165611

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Project description:BackgroundUnderweight prevalence continues to be major public health challenge worldwide, particularly in developing countries like Pakistan. This study is focused on socio-economic and demographic aspects of underweight prevalence among children under-five in Punjab.MethodsIn this study, several socioeconomic and demographic factors are considered using MICS-4 data-set. Only those variables which are usually described in the nutritional studies of children were picked. Covariates include: the age of children, sex of the children, age of mother, total number of children born to women, family wealth index quintile, source of drinking water, type of sanitation, place of residence, parents' education and occupation. All Categorical variables are effect coded. The child's age and the mother's age are assumed to be nonlinear, geographical region is spatial effect, while other variables are parametric in nature. Since, the response is binary, covariate comprises linear terms, nonlinear effects of continues covariates and geographic effects, so we have use Geo-additive models (based on Fully Bayesian approach) with binomial family under logit link. Statistical analysis is performed on Statistical package R using Bayes X and R2 Bayes X Libraries.ResultsUnderweight status of children was found to be positively associated with number of under-five children in household, total number of children ever born to women and age of mother when the child was born. Whereas, it negatively associated with place of residence, parent's education and family wealth index quintile. On the regional effect, the Southern Punjab has higher prevalence of underweight compared to Central and Northern Punjab.ConclusionSimilarity of our results with several other studies demonstrate that the Geo-additive models are an ideal substitute of other statistical models to analyze the underweight prevalence among children. Moreover, our findings suggest the Punjab Government, to introduce target-oriented programs such as poverty reduction and enhancement of education and health facilities for poor population and disadvantaged regions, especially Southern Punjab.

Project description:Background: The SARS-CoV-2 pandemic has disproportionately affected racial and ethnic minority communities across the United States. We sought to disentangle individual and census tract-level sociodemographic and economic factors associated with these disparities. Methods and Findings: All adults tested for SARS-CoV-2 between February 1 and June 21, 2020 were geocoded to a census tract based on their address; hospital employees and individuals with invalid addresses were excluded. Individual (age, sex, race/ethnicity, preferred language, insurance) and census tract-level (demographics, insurance, income, education, employment, occupation, household crowding and occupancy, built home environment, and transportation) variables were analyzed using linear mixed models predicting infection, hospitalization, and death from SARS-CoV-2. Among 57,865 individuals, per capita testing rates, individual (older age, male sex, non-White race, non-English preferred language, and non-private insurance), and census tract-level (increased population density, higher household occupancy, and lower education) measures were associated with likelihood of infection. Among those infected, individual age, sex, race, language, and insurance, and census tract-level measures of lower education, more multi-family homes, and extreme household crowding were associated with increased likelihood of hospitalization, while higher per capita testing rates were associated with decreased likelihood. Only individual-level variables (older age, male sex, Medicare insurance) were associated with increased mortality among those hospitalized. Conclusions: This study of the first wave of the SARS-CoV-2 pandemic in a major U.S. city presents the cascade of outcomes following SARS-CoV-2 infection within a large, multi-ethnic cohort. SARS-CoV-2 infection and hospitalization rates, but not death rates among those hospitalized, are related to census tract-level socioeconomic characteristics including lower educational attainment and higher household crowding and occupancy, but not neighborhood measures of race, independent of individual factors.

Project description:ImportanceDiabetic retinopathy (DR) is a leading cause of vision loss worldwide. As the incidence of both type 1 and type 2 diabetes among youths continues to increase around the world, understanding the factors associated with the development of DR in this age group is important.ObjectiveTo identify factors associated with DR among children, adolescents, and young adults with type 1 or type 2 diabetes in the US.Design, setting, and participantsThis cross-sectional study pooled data from 2 large academic pediatric centers in the US (Baylor College of Medicine/Texas Children's Hospital [BCM/TCH] Diabetes and Endocrine Care Center and Johns Hopkins University [JHU] Pediatric Diabetes Center) to form a diverse population for analysis. Data were collected prospectively at the JHU center (via point-of-care screening using fundus photography) from December 3, 2018, to November 1, 2019, and retrospectively at the BCM/TCH center (via electronic health records of patients who received point-of-care screening using retinal cameras between June 1, 2016, and May 31, 2019). A total of 1640 individuals aged 5 to 21 years with type 1 or type 2 diabetes (308 participants from the JHU center and 1332 participants from the BCM/TCH center) completed DR screening and had gradable images.Main outcome and measuresPrevalence of DR, as identified on fundus photography, and factors associated with DR.ResultsAmong 1640 participants (mean [SD] age, 15.7 [3.6] years; 867 female individuals [52.9%]), 1216 (74.1%) had type 1 diabetes, and 416 (25.4%) had type 2 diabetes. A total of 506 participants (30.9%) were Hispanic, 384 (23.4%) were non-Hispanic Black or African American, 647 (39.5%) were non-Hispanic White, and 103 (6.3%) were of other races or ethnicities (1 was American Indian or Alaska Native, 50 were Asian, 1 was Native Hawaiian or Pacific Islander, and 51 did not specify race or ethnicity, specified other race or ethnicity, or had unavailable data on race or ethnicity). Overall, 558 of 1216 patients (45.9%) with type 1 diabetes used an insulin pump, and 5 of 416 patients (1.2%) with type 2 diabetes used an insulin pump. Diabetic retinopathy was found in 57 of 1640 patients (3.5%). Patients with DR vs without DR had a greater duration of diabetes (mean [SD], 9.4 [4.4] years vs 6.6 [4.4] years; P < .001) and higher hemoglobin A1c (HbA1c) levels (mean [SD], 10.3% [2.4%] vs 9.2% [2.1%]; P < .001). Among those with type 1 diabetes, insulin pump use was associated with a lower likelihood of DR after adjusting for race and ethnicity, insurance status, diabetes duration, and HbA1c level (odds ratio [OR], 0.43; 95% CI, 0.20-0.93; P = .03). The likelihood of having DR was 2.1 times higher among Black or African American participants compared with White participants (OR, 2.12; 95% CI, 1.12-4.01; P = .02); this difference was no longer significant after adjusting for duration of diabetes, insurance status, insulin pump use (among patients with type 1 diabetes only), and mean HbA1c level (type 1 diabetes: OR, 1.79; 95% CI, 0.83-3.89; P = .14; type 2 diabetes: OR, 1.08; 95% CI, 0.30-3.85; P = .91).Conclusions and relevanceThis study found that although the duration of diabetes and suboptimal glycemic control have long been associated with DR, insulin pump use (among those with type 1 diabetes) was independently associated with a lower likelihood of DR, which is likely owing to decreased glycemic variability and increased time in range (ie, the percentage of time blood glucose levels remain within the 70-180 mg/dL range). Black or African American race was found to be associated with DR in the univariable analysis but not in the multivariable analysis, which may represent disparities in access to diabetes technologies and care.

Project description:ImportanceCardiovascular disease and risk factors represent a major and increasing burden of death and disability in India, although socioeconomic aspects have been debated in recent years.ObjectiveTo conduct a comprehensive equity analysis of the socioeconomic gradients and distribution of diabetes, hypertension, and obesity in India using the latest national data set.Design, setting, and participantsCross-sectional study of data originating from the fourth Indian National Family Health Survey collected from January 20, 2015, to December 4, 2016. The study population was based on a nationally representative cross-sectional sample of women aged 15 to 49 years and men aged 15 to 54 years in India, with a response rate of 97% and 92% among eligible women and men, respectively. Biomarker sampling of survey respondents captured height, weight, blood pressure, and random blood glucose levels. Markers of socioeconomic status (SES) were household wealth, education, and social caste. Descriptive analyses and logistic regression models that account for multistage survey design and sampling weights were estimated.Main outcomes and measuresDiabetes, hypertension, and obesity assessed by predetermined thresholds based on biomarker sampling or current medication were the primary outcomes.ResultsThe survey covered 757 958 individuals (weighted prevalence of 51.2% female). The overall prevalence of diabetes, hypertension, and obesity in the sample was 2.9%, 14.4% and 9.7%, respectively. Positive socioeconomic gradients were observed by household wealth, education, and social caste, and in a majority of states. The magnitude of the SES gradient was strongest for obesity (adjusted odds ratio for highest SES quintile vs lowest, 8.76; 95% CI, 7.70-9.95), followed by diabetes (adjusted odds ratio, 2.31; 95% CI, 1.88-2.85) and hypertension (adjusted odds ratio, 1.58; 95% CI, 1.45-1.72) (P < .001 for all associations). Analyses of the socioeconomic distribution indicated that between 70% and 90% of the population burden of diabetes, hypertension, and obesity was among the higher SES groups, and this figure was similar across states.Conclusions and relevanceCardiovascular risk factors have an uneven distribution in India. Prevention and treatment strategies should reflect the distribution of the risk factor burden.

Project description:Knowledge on the occurrence of multimorbidity is important from the viewpoint of public policies, as this condition increases the consumption of medicines as well as the utilization and expenses of health services, affecting life quality of the population. The objective of this study was to estimate prevalence of self-reported multimorbidity in Brazilian adults (?18 years old) according to socioeconomic and demographic characteristics. A descriptive study is presented herein, based on data from the National Health Survey, which was a household-based survey carried out in Brazil in 2013. Data on 60,202 adult participants over the age of 18 were included. Prevalences and its respective confidence intervals (95%) were estimated according to sex, age, education level, marital status, self-reported skin color, area of residence, occupation and federative units (states). Poisson regression models univariate and multivariate were used to evaluate the association between socioeconomic and demographic variables with multimorbidity. To observe the combinations of chronic conditions the most common groups in pairs, trios, quartets and quintets of chronic diseases were observed. The prevalence of multimorbidity was 23.6% and was higher among women, in individuals over 60 years of age, people with low educational levels, people living with partner, in urban areas and among unemployed persons. The states of the South and Southeast regions presented higher prevalence. The most common groups of chronic diseases were metabolic and musculoskeletal diseases. The results demonstrated high prevalence of multimorbidity in Brazil. The study also revealed that a considerable share of the economically active population presented two or more chronic diseases. Data of this research indicated that socioeconomic and demographic aspects must be considered during the planning of health services and development of prevention and treatment strategies for chronic diseases, and consequently, multimorbidity.

Dataset Information

Prevalence of Gestational Diabetes in India by Individual Socioeconomic, Demographic, and Clinical Factors.

Publications

Prevalence of Gestational Diabetes in India by Individual Socioeconomic, Demographic, and Clinical Factors.

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