Factors affecting External causes of deaths among adults (15–59 years) in South Indian states: A study using Bayesian model on National Family Health Survey-4 (2015–16) data

This study uses data from the 1992–93 National Family Health Survey to assess trends in consanguinity in the South Indian states of Andhra Pradesh, Karnataka, Kerala and Tamil Nadu. In Kerala, the frequency of consanguineous marriages is very low and one type of preferred marriage of the Dravidian marriage system – uncle–niece marriage – is conspicuously absent. In the other states of South India, consanguinity and the coefficient of inbreeding are high. While no change in consanguinity is observed during the past three to four decades in Karnataka, a definite decline is observed in Andhra Pradesh and Tamil Nadu. Due to recent changes in the demographic and social situation in these states, this decline in consanguinity is likely to continue.

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Patterns and distribution of tobacco consumption in India: cross sectional multilevel evidence from the 1998-9 national family health survey

BMJ ◽

10.1136/bmj.328.7443.801 ◽

2004 ◽

Vol 328 (7443) ◽

pp. 801-806 ◽

Cited By ~ 106

Author(s):

S V Subramanian ◽

Shailen Nandy ◽

Michelle Kelly ◽

Dave Gordon ◽

George Davey Smith

Keyword(s):

Health Survey ◽

Family Health ◽

Postgraduate Education ◽

Tobacco Consumption ◽

National Family Health Survey ◽

Cross Sectional ◽

Indian States ◽

Chewing Tobacco ◽

Household Level ◽

National Family

AbstractObjective To investigate the demographic, socioeconomic, and geographical distribution of tobacco consumption in India.Design Multilevel cross sectional analysis of the 1998-9 Indian national family health survey of 301 984 individuals in 92 447 households in 3215 villages in 440 districts in 26 states.Setting Indian states.Participants 301 984 adults (≥ 18 years).Main outcome measures Dichotomous variable for smoking and chewing tobacco for each respondent (1 if yes, 0 if no) as well as a combined measure of whether an individual smokes, chews tobacco, or both.Results Smoking and chewing tobacco are systematically associated with socioeconomic markers at the individual and household level. Individuals with no education are 2.69 times more likely to smoke and chew tobacco than those with postgraduate education. Households belonging to the lowest fifth of a standard of living index were 2.54 times more likely to consume tobacco than those in the highest fifth. Scheduled tribes (odds ratio 1.23, 95% confidence interval 1.18 to 1.29) and scheduled castes (1.19, 1.16 to 1.23) were more likely to consume tobacco than other caste groups. The socioeconomic differences are more marked for smoking than for chewing tobacco. Socioeconomic markers and demographic characteristics of individuals and households do not account fully for the differences at the level of state, district, and village in smoking and chewing tobacco, with state accounting for the bulk of the variation in tobacco consumption.Conclusion The distribution of tobacco consumption is likely to maintain, and perhaps increase, the current considerable socioeconomic differentials in health in India. Interventions aimed at influencing change in tobacco consumption should consider the socioeconomic and geographical determinants of people's susceptibility to consume tobacco.

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Scenario of under nutrition among under five years children in India and its states: findings from National Family Health Survey

International Journal of Community Medicine and Public Health ◽

10.18203/2394-6040.ijcmph20203382 ◽

2020 ◽

Vol 7 (8) ◽

pp. 3087

Author(s):

Piyush Kumar Mishra ◽

Vijay Kumar Mishra

Keyword(s):

Logistic Regression ◽

Mass Media ◽

Health Survey ◽

Family Health ◽

National Family Health Survey ◽

Multiple Logistic Regression ◽

Indian States ◽

Under Nutrition ◽

National Family ◽

Current Scenario

Background: The status of undernutrition among under 5years children living in India is a public health concern. Our study identified contributed factors of undernutrition and current scenario of undernutrition among children living across Indian states. Objective of the study was to know the current scenario of undernutrition among under 5 years children across Indian states and to examine the associated factors with this.Methods: This study used data from 4th round of National Family Health Survey (NFHS-4) that was coordinated by International Institute for Population Sciences (IIPS) during 2015-16 under the ministry of health and family welfare, GoI. Multiple logistic regression model was done to study the association between outcome (under nutrition) and socio-economic and bio-medical predictors.Results: This study identified four empowered action group (EAG) states as the problem states because of the greater number of undernourished children living in these states than other Indian states. The children whose mothers were fully exposed to mass media like newspapers/radio/television, have lower prevalence of undernutrition (50.6%). The results of multiple logistic regression revealed that the children belonging to poorest households were 2 times more likely [OR-CI, 2.35 (2.27-2.44)] to be undernourished than those belonging to richest.Conclusions: Undernutrition can be reduced through awareness with the help of mass media, providing higher education to women and reducing socio-economic inequalities. It is necessary to re-think about nutritional policy with respect to children under 5 years and frame a full proof implementation plan to reduce undernutrition in India.

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Global hunger index of India based on National family health survey-IV with special reference to some states and critical review

International Journal of Community Medicine and Public Health ◽

10.18203/2394-6040.ijcmph20173323 ◽

2017 ◽

Vol 4 (8) ◽

pp. 2783

Author(s):

Ashish Wasudeo Khobragade ◽

K. Rajan

Keyword(s):

Health Survey ◽

Data Entry ◽

Family Health ◽

Secondary Data ◽

State Level ◽

National Family Health Survey ◽

Indian States ◽

National Family ◽

Different Types ◽

New Formula

Background: India is facing serious hunger situation now. Factors responsible for this hunger situation are different. This study focuses on hunger situation in 4 different states of India and remedial measures.Methods: Secondary data was collected from National Family Health Survey-IV (NFHS). Data entry was done in excel sheet. GHI was calculated using new formula given by IFPRI.Results: There are wide disparities in hunger situation in Indian states. Madhya Pradesh is in alarming state of hunger.Conclusions: Hunger situation in Indian states varies from states to states. Different types of interventions are required at each state level to improve the overall hunger situation.

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Spatial Pattern of Maternal Health in Northeastern States, India-evidence from national family health survey 4 (2015-16)

Asian Pacific Journal of Health Sciences ◽

10.21276/apjhs.2017.4.2.25 ◽

2017 ◽

Vol 4 (2) ◽

pp. 147-156 ◽

Cited By ~ 1

Author(s):

Kh. Jitenkumar Singh ◽

◽

Swati Kadian ◽

Amandeep Kaur ◽

Kiran Saini ◽

...

Keyword(s):

Maternal Health ◽

Spatial Pattern ◽

Health Survey ◽

Family Health ◽

National Family Health Survey ◽

National Family

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Inequalities in utilisation of maternal health services in urban India: Evidences from national family health survey-4

Clinical Epidemiology and Global Health ◽

10.1016/j.cegh.2020.11.005 ◽

2021 ◽

Vol 10 ◽

pp. 100672

Author(s):

Balhasan Ali ◽

Paramita Debnath ◽

Tarique Anwar

Keyword(s):

Maternal Health ◽

Health Services ◽

Health Survey ◽

Family Health ◽

Maternal Health Services ◽

National Family Health Survey ◽

Urban India ◽

National Family

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Missed opportunities for delivering nutrition interventions in first 1000 days of life in India: insights from the National Family Health Survey, 2006 and 2016

BMJ Global Health ◽

10.1136/bmjgh-2020-003717 ◽

2021 ◽

Vol 6 (2) ◽

pp. e003717

Author(s):

Phuong Hong Nguyen ◽

Rasmi Avula ◽

Lan Mai Tran ◽

Vani Sethi ◽

Alok Kumar ◽

...

Keyword(s):

Health Survey ◽

Urban Areas ◽

Family Health ◽

Universal Coverage ◽

National Family Health Survey ◽

Nutrition Interventions ◽

Missed Opportunities ◽

Health And Nutrition ◽

National Family ◽

Opportunity Gaps

ObjectivesExisting health and community nutrition systems have the potential to deliver many nutrition interventions. However, the coverage of nutrition interventions across the delivery platforms of these systems has not been uniform. We (1) examined the opportunity gaps between delivery platforms and corresponding nutrition interventions through the continuum of care in India between 2006 and 2016 and and (2) assessed inequalities in these opportunity gaps.MethodsWe used two rounds of the National Family Health Survey data from 2005 to 2006 and 2015–2016 (n=36 850 and 190 898 mother–child dyads, respectively). We examine the opportunity gaps over time for seven nutrition interventions and their associated delivery platforms at national and state levels. We assessed equality and changes in equality between 2006 and 2016 for opportunity gaps by education, residence, socioeconomic status (SES), public and private platforms.ResultsCoverage of nutrition interventions was consistently lower than the reach of their associated delivery platforms; opportunity gaps ranging from 9 to 32 percentage points (pp) during the pregnancy, 17 pp during delivery and 9–26 pp during childhood in 2006. Between 2006 and 2016, coverage improved for most indicators, but coverage increases for nutrition interventions was lower than for associated delivery platforms. The opportunity gaps were larger among women with higher education (22–57 pp in 2016), higher SES status and living in urban areas (23–57 pp), despite higher coverage of most interventions and the delivery platforms among these groups. Opportunity gaps vary tremendously by state with the highest gaps observed in Tripura, Andaman and Nicobar islands, and Punjab for different indicators.ConclusionsIndia’s progress in coverage of health and nutrition interventions in the last decade is promising, but both opportunity and equality gaps remained. It is critical to close these gaps by addressing policy and programmatic delivery systems bottlenecks to achieve universal coverage for both health and nutrition within the delivery system.

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