Nutritional status of preschool children in Andaman and Nicobar Islands and food insecurity, food groups, and nutrient consumption among population

Background: Childhood undernutrition is a public health concern in India. But on such a serious issue, there are no data available from the Union Territory of Andaman and Nicobar (A and N) Islands. Objectives: Present study was designed to know the prevalence of food insecurity, to estimate food group and nutrient intake among the community, and undernutrition and clinical signs of micronutrient deficiency among the preschool children of A and N islands. Materials and Methods: Multistage random sampling was followed to select the households containing children aged 6-59 months. In the selected households' sociodemographic particulars, Household Food Insecurity Access Scale (HFIAS), among preschoolers the weight and height were recorded along with the documentation of clinical signs of micronutrient deficiency, morbidities suffered over previous fortnight, and measurement of hemoglobin. Diet survey was carried out in every fourth household. Results: A total of 1259 preschoolers residing in 1082 households were examined, HFIAS was measured in 710 households in Andaman group of islands and diet survey was conducted in 290 households. The prevalence of undernutrition was around 27%, stunting was 36%, and anemia was around 81%. Undernutrition and anemia prevalence were significantly low among Nicobarese children. After adjusting for all the determinants, tribal in domicile had favorable outcome [odds ratio (OR): 0.28 (0.18, 0.43)], while below poverty line family had adverse outcome on undernutrition [OR: 1.72 (1.20, 2.46)]. Conclusion: Though the prevalence of undernutrition is relatively low in the islands, but high prevalence of anemia needs to be addressed. Nicobarese children fare better in almost all indicators of nutritional well-being except for stunting

Chronic disease concordance within Indian households: A cross-sectional study

Background: The household is a potentially important but understudied unit of analysis and intervention in chronic disease research. We sought to estimate the association between living with someone with a chronic condition and one’s own chronic condition status. Methods and findings We conducted a cross-sectional analysis of population-based household- and individual-level data collected in 4 socioculturally and geographically diverse settings across rural and urban India in 2013 and 2014. Of 10,703 adults ages 18 years and older with coresiding household members surveyed, data from 7,522 adults (mean age 39 years) in 2,574 households with complete covariate information were analyzed. The main outcome measures were diabetes (fasting plasma glucose ≥ 126 mg/dL or taking medication), common mental disorder (General Health Questionnaire score ≥ 12), hypertension (blood pressure ≥ 140/90 mmHg or taking medication), obesity (body mass index ≥ 30 kg/m2), and high cholesterol (total blood cholesterol ≥ 240 mg/dL or taking medication). Logistic regression with generalized estimating equations was used to model associations with adjustment for a participant’s age, sex, education, marital status, religion, and study site. Inverse probability weighting was applied to account for missing data. We found that 44% of adults had 1 or more of the chronic conditions examined. Irrespective of familial relationship, adults who resided with another adult with any chronic condition had 29% higher adjusted relative odds of having 1 or more chronic conditions themselves (adjusted odds ratio [aOR] = 1.29; 95% confidence interval [95% CI] 1.10–1.50). We also observed positive statistically significant associations of diabetes, common mental disorder, and hypertension with any chronic condition (aORs ranging from 1.19 to 1.61) in the analysis of all coresiding household members. Associations, however, were stronger for concordance of certain chronic conditions among coresiding household members. Specifically, we observed positive statistically significant associations between living with another adult with diabetes (aOR = 1.60; 95% CI 1.23–2.07), common mental disorder (aOR = 2.69; 95% CI 2.12–3.42), or obesity (aOR = 1.82; 95% CI 1.33–2.50) and having the same condition. Among separate analyses of dyads of parents and their adult children and dyads of spouses, the concordance between the chronic disease status was striking. The associations between common mental disorder, hypertension, obesity, and high cholesterol in parents and those same conditions in their adult children were aOR = 2.20 (95% CI 1.28–3.77), 1.58 (95% CI 1.15–2.16), 4.99 (95% CI 2.71–9.20), and 2.57 (95% CI 1.15–5.73), respectively. The associations between diabetes and common mental disorder in husbands and those same conditions in their wives were aORs = 2.28 (95% CI 1.52–3.42) and 3.01 (95% CI 2.01–4.52), respectively. Relative odds were raised even across different chronic condition phenotypes; specifically, we observed positive statistically significant associations between hypertension and obesity in the total sample of all coresiding adults (aOR = 1.24; 95% CI 1.02–1.52), high cholesterol and diabetes in the adult-parent sample (aOR = 2.02; 95% CI 1.08–3.78), and hypertension and diabetes in the spousal sample (aOR = 1.51; 95% CI 1.05–2.17). Of all associations examined, only the relationship between hypertension and diabetes in the adult-parent dyads was statistically significantly negative (aOR = 0.62; 95% CI 0.40–0.94). Relatively small samples in the dyadic analysis and site-specific analysis call for caution in interpreting qualitative differences between associations among different dyad types and geographical locations. Because of the cross-sectional nature of the analysis, the findings do not provide information on the etiology of incident chronic conditions among household members. Conclusions: We observed strong concordance of chronic conditions within coresiding adults across diverse settings in India. These data provide early evidence that a household-based approach to chronic disease research may advance public health strategies to prevent and control chronic conditions. Trial registration Clinical Trials Registry India CTRI/2013/10/004049; http://ctri.nic.in/Clinicaltrials/login.ph

Outbreak of Chikungunya Fever, Dakshina Kannada District, South India, 2008

The outbreak of chikungunya fever that surfaced in India during late 2005 has affected more than 1.56 million people, spread to more than 17 states/union territories, and is still ongoing. Many of these areas are dengue- and leptospirosis-endemic settings. We carried out a cross-sectional survey in one such chikungunya-affected location in Dakshina Kannada District of Karnataka State to estimate the magnitude of the epidemic and the proportion of chikungunya virus (CHIKV) infections that remained clinically inapparent. The seropositivity for CHIKV infection was 62.2%, and the attack rate of confirmed CHIK fever was 58.3%. The proportion of inapparent CHIKV infection was 6.3%. The increasing trend in the seropositivity and attack rate of CHIKV infection with age group was statistically significant. The present study is an indicator of the magnitude of the ongoing outbreak of CHIKV infection in India that started during 2005–2006

Adjusted association between living with someone with a given chronic condition and having that same or another chronic condition (<i>n</i> = 7,572).

<p>Adjusted association between living with someone with a given chronic condition and having that same or another chronic condition (<i>n</i> = 7,572).</p

Site-specific adjusted relative odds (95% confidence interval) of having a chronic condition if any other member of the household has that same chronic condition (reference: no other member of the household has that same condition) and test for interaction between sites.

<p>Site-specific associations were computed by including an interaction term between the site and the exposure condition. The <i>P</i> values shown are from generalized score tests for Type III contrasts for the site x exposure interaction term. The horizontal line marks the null value. Madhya Pradesh data were excluded from the common mental disorder analysis because of poor performance of the survey tool. Chronic conditions were defined as follows: diabetes (prior diagnosis, fasting plasma glucose ≥ 126 mg/dL, or taking medication); common mental disorder (General Health Questionnaire score ≥ 12); hypertension (prior diagnosis, blood pressure ≥ 140/90 mmHg, or taking medication); obesity (body mass index ≥ 30 kg/m²); and high cholesterol (prior diagnosis, total blood cholesterol ≥ 240 mg/dL, or taking medication). See <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002395#pmed.1002395.s003" target="_blank">S3 Table</a> for these data in table form.</p

Adjusted association between living with a parent with a given chronic condition and having that same or another chronic condition (<i>n</i> = 1,660).

<p>Adjusted association between living with a parent with a given chronic condition and having that same or another chronic condition (<i>n</i> = 1,660).</p

Characteristics of the analytic sample.

<p>Characteristics of the analytic sample.</p