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India is currently one of the most demographically diverse regions of the world. Fertility and mortality rates are known to show considerable variation at the level of regions, states and districts. Little is known however, about the spatial variations of the contraceptive usage—a critical variable that is relevant to fertility as well as health policy. This paper uses data from four national population-based household surveys conducted between 1998 and 2016 to explore district-level variations in the contraceptive prevalence rate. We find no clear evidence of convergence. The gap between the best and worst performing districts is more than 70 percent across the four rounds and does not diminish over time. We also find considerable evidence of spatial clustering across districts. Districts with high prevalence concentrate in Southern states and more recently, in the Northeast of the country. Our analysis suggests that female literacy and health care infrastructure are important correlates of spatial clusters. This suggests that investments in women’s human capital and health-care infrastructure play a role in expanding women’s opportunities to time their births.

In this paper, we examine patterns of self-reported diagnosis of noncommunicable diseases (NCDs) and prevalences of algorithm/measured test-based, undiagnosed, and untreated NCDs in China, Ghana, India, Mexico, Russia, and South Africa. Nationally representative samples of older adults aged ≥50 years were analyzed from wave 1 of the World Health Organization's Study on Global Ageing and Adult Health (2007–2010; n = 34,149). Analyses focused on 6 conditions: angina, arthritis, asthma, chronic lung disease, depression, and hypertension. Outcomes for these NCDs were: 1) self-reported disease, 2) algorithm/measured test-based disease, 3) undiagnosed disease, and 4) untreated disease. Algorithm/measured test-based prevalence of NCDs was much higher than self-reported prevalence in all 6 countries, indicating underestimation of NCD prevalence in low- and middle-income countries. Undiagnosed prevalence of NCDs was highest for hypertension, ranging from 19.7% (95% confidence interval (CI): 18.1, 21.3) in India to 49.6% (95% CI: 46.2, 53.0) in South Africa. The proportion untreated among all diseases was highest for depression, ranging from 69.5% (95% CI: 57.1, 81.9) in South Africa to 93.2% (95% CI: 90.1, 95.7) in India. Higher levels of education and wealth significantly reduced the odds of an undiagnosed condition and untreated morbidity. A high prevalence of undiagnosed NCDs and an even higher proportion of untreated NCDs highlights the inadequacies in diagnosis and management of NCDs in local health-care systems.

Background Client-centric quality of care (QoC) in family planning (FP) services are imperative for contraceptive method adoption and continuation. Less is known about the choice of contraceptive method in India beyond responses to the three common questions regarding method information, asked in demographic and health surveys. This study argues for appropriate measurement of method choice and assesses its levels and correlates in rural India. Methods A cross-sectional study was conducted with new acceptors of family planning method (N = 454) recruited from public and private health facilities in rural Bihar and Uttar Pradesh, the two most populous states in India. The key quality of care indicator ‘method choice’ was assessed using four key questions from client-provider interactions that help in making a choice about a particular method: (1) whether the provider asked the client about their preferred method, (2) whether the provider told the client about at least one additional method, (3) whether the client received information without any single method being promoted by the provider, and (4) client’s perception about receipt of method choice. The definition of method choice in this study included women who responded “yes” to all four questions in the survey. The relationship between contraceptive communication and receipt of method choice was assessed using logistic regression analyses, after adjusting for socio-demographic characteristics of the respondents. Results Although 62% of clients responded to a global question and reported that they received the method of their choice, only 28% received it based on responses about client-provider interactions. Receipt of the information on side-effects of the selected method (Adjusted Odds Ratio [AOR]: 7.4, 95% Confidence Interval [CI]: 3.96–13.86) and facility readiness to provide a range of contraceptive choice (AOR: 2.67, 95% CI: 1.48–4.83) were significantly associated with receipt of method choice. Conclusions Findings demonstrated that women’s choice of contraceptive could be improved in rural India if providers give full information prior to and during the acceptance of a method and if facilities are equipped to provide a range of choice of contraceptive methods.

Background In 2014, 16 women died following female sterilization operations in Bilaspur, a district in central India. In addition to those 16 deaths, 70 women were hospitalized for critical conditions (Sharma, Lancet 384,2014). Although the government of India’s guidelines for female sterilization mandate infection prevention practices, little is known about the extent of infection prevention preparedness and practice during sterilization procedures that are part of the country’s primary health care services. This study assesses facility readiness for infection prevention and adherence to infection prevention practices during female sterilization procedures in rural northern India. Method The data for this study were collected in 2016–2017 as part of a family planning quality of care survey in selected public health facilities in Bihar (n = 100), and public (n = 120) and private health facilities (n = 97) in Uttar Pradesh. Descriptive analysis examined the extent of facility readiness for infection prevention (availability of handwashing facilities, new or sterilized gloves, antiseptic lotion, and equipment for sterilization). Correlation and multivariate statistical methods were used to examine the role of facility readiness and provider behaviors on infection prevention practices during female sterilization. Result Across the three health sectors, 62% of facilities featured all four infection prevention components. Sterilized equipment was lacking in all three health sectors. In facilities with all four components, provider adherence to infection prevention practices occurred in only 68% of female sterilization procedures. In Bihar, 76% of public health facilities evinced all four components of infection prevention, and in those facilities provider’s adherence to infection prevention practices was almost universal. In Uttar Pradesh, where only 55% of public health facilities had all four components, provider adherence to infection prevention practices occurred in only 43% of female sterilization procedures. Conclusion The findings suggest that facility preparedness for infection prevention does play an important role in provider adherence to infection prevention practices. This phenomenon is not universal, however. Not all doctors from facilities prepared for infection prevention adhere to the practices, highlighting the need to change provider attitudes. Unprepared facilities need to procure required equipment and supplies to ensure the universal practice of infection prevention.

This paper describes overall socioeconomic gradients and the age patterns of socioeconomic gradients of health of Indian adults for multiple health indicators encompassing the multiple aspects of health. Cross-sectional data on 11,230 Indians aged 18 years and older from the WHO-SAGE India Wave 1, 2007 were analyzed. Multivariate logit models were estimated to examine effects of socioeconomic status (education and household wealth) and age on four health domains: self-rated health, self-reported functioning, chronic diseases, and biological health measures. Results show that socioeconomic status (SES) was negatively associated with prevalence of each health measure but with considerable heterogeneity across age groups. Results for hypertension and COPD were inconclusive. SES effects are significant while adjusting for background characteristics and health risk factors. The age patterns of SES gradient of health depict divergence with age, however, no conclusive age pattern emerged for biological markers. Overall, results in this paper dispelled the conclusion of negative SES-health association found in some previous Indian studies and reinforced the hypothesis of positive association of SES with health for Indian adults. Higher prevalence of negative health outcomes and SES disparities of health outcomes among older age-groups highlight need for inclusive and focused health care interventions for older adults across socioeconomic spectrum.

Exposure to air pollution produced by cooking is common in developing countries, and represents a potentially avoidable cause of lung disease. Cross-sectional data were collected by the World Health Organization's Study on Global AGEing and Adult Health conducted in India between 2007 and 2010. Exposure to biomass cooking was also associated with a decrease in forced expiratory volume in 1 s (FEV1) (-70 ml, 95%CI -111 to -30) and FEV1/FVC (forced vital capacity) ratio (-0.025, 95%CI -0.035 to -0.015) compared to those who were not exposed. These associations were predominantly observed in males (P < 0.05 for interaction analyses). Intervention studies using non-biomass fuels in India are required to ascertain potential respiratory health benefits.

Background Chronic diseases contribute a large share of disease burden in low- and middle-income countries (LMICs). Chronic diseases have a tendency to occur simultaneously and where there are two or more such conditions, this is termed as ‘multimorbidity’. Multimorbidity is associated with adverse health outcomes, but limited research has been undertaken in LMICs. Therefore, this study examines the prevalence and correlates of multimorbidity as well as the associations between multimorbidity and self-rated health, activities of daily living (ADLs), quality of life, and depression across six LMICs. Methods Data was obtained from the WHO’s Study on global AGEing and adult health (SAGE) Wave-1 (2007/10). This was a cross-sectional population based survey performed in LMICs, namely China, Ghana, India, Mexico, Russia, and South Africa, including 42,236 adults aged 18 years and older. Multimorbidity was measured as the simultaneous presence of two or more of eight chronic conditions including angina pectoris, arthritis, asthma, chronic lung disease, diabetes mellitus, hypertension, stroke, and vision impairment. Associations with four health outcomes were examined, namely ADL limitation, self-rated health, depression, and a quality of life index. Random-intercept multilevel regression models were used on pooled data from the six countries. Results The prevalence of morbidity and multimorbidity was 54.2 % and 21.9 %, respectively, in the pooled sample of six countries. Russia had the highest prevalence of multimorbidity (34.7 %) whereas China had the lowest (20.3 %). The likelihood of multimorbidity was higher in older age groups and was lower in those with higher socioeconomic status. In the pooled sample, the prevalence of 1+ ADL limitation was 14 %, depression 5.7 %, self-rated poor health 11.6 %, and mean quality of life score was 54.4. Substantial cross-country variations were seen in the four health outcome measures. The prevalence of 1+ ADL limitation, poor self-rated health, and depression increased whereas quality of life declined markedly with an increase in number of diseases. Conclusions Findings highlight the challenge of multimorbidity in LMICs, particularly among the lower socioeconomic groups, and the pressing need for reorientation of health care resources considering the distribution of multimorbidity and its adverse effect on health outcomes. Electronic supplementary material The online version of this article (doi:10.1186/s12916-015-0402-8) contains supplementary material, which is available to authorized users.

Socioeconomic status (SES) has occupied a central stage in predicting the health of the population, even in old age the association continues; however, the role childhood SES remains unclear in developing countries. Using the data of aged 50 and above drawn from WHO-SAGE-20070-10 wave 1, this study assess the effect of childhood SES and current SES on subjective health measures in six LMICs: India, China, Ghana, Mexico, Russia and South Africa. Parental education is used as the indicator of childhood SES and household wealth and individual education are used as the measures of current SES. Poor self-rated health (SRH) and limitations in activities of daily living (ADLs) are used as the measure of subjective health. Logistic regression analysis is used to examine the effect of indicators of adult and childhood SES on poor SRH and ADL limitations. Results show considerable variations across nations in the prevalence of poor health status. The poor SRH was high in Russia and India. Also, the larger proportion of older adults in India, Ghana, Mexico and South Africa had 1 + ADL. Higher socioeconomic status is associated with less poor health and ADL limitations. Further, our results suggest that the mother’s education had a significant and independent effect on self-rated health and ADL limitations. Our findings confirm the association of education, wealth and mother’s education with subjective health measures, moreover the association with self-rated health stronger than the 1 + ADL limitation. This result therefore reiterate the importance of childhood and current SES on health, thus suggest the life course intervention to improve the health of the older population in LMICs.

This paper examines the prevalence and determinants of multiple chronic diseases and their association with the self-rated health, functional health and quality of life among adults in six SAGE countries: China, India, Russia, South Africa Mexico and Ghana. We use ADL and IADL activities as measures of functional health and WHOQoL index as a measure of quality of life. Poisson regression models are estimated to understand the social determinants of multiple chronic diseases. Logit models and OLS are estimated to examine the association between multiple chronic morbidities and self-rated health, functional health and quality of life. Russia had the highest prevalence of multi-morbidity (32.8%, 95%CI=25.5-41.1) followed by South Africa (22%, 95%CI=17.7-26.9); the other four countries had prevalence of multi-morbidity around 21%. Measures of socioeconomic status: education and wealth were found negatively associated with the number of chronic diseases. Higher number of chronic conditions was associated with the poorer self rated health, functional health and WHOQoL.

Objectives: This paper describes the age patterns of socioeconomic gradients of health of Indian adults for multiple health indicators encompassing the multidimensional nature of health. Methods: Cross-sectional data on 11,230 Indians aged 18-plus from the WHO-SAGE India Wave 1, 2007 is used. Multivariate logit models were estimated to examine the effects of socioeconomic status (education and household wealth) and age on four health measures: self-rated health, self-reporting functioning, chronic diseases, and performance-based health indicators. Findings: Socioeconomic status was positively associated with each health measure but with considerable heterogeneity across age groups. SES relationship with biomarkers (hypertension and COPD) was inconclusive. SES effects are significant while adjusting for background characteristics and health risk factors. The age patterns of SES gradient of health depict divergence with age, however, no conclusive age pattern emerged for performance-based health indicators. Discussion: Overall, results in this paper dispelled the conclusion of negative SES-health association found in some previous Indian studies and reinforced the hypothesis of positive association of SES with health for Indian adults. Higher prevalence of negative health outcomes and SES disparities of health outcomes among older age-groups highlight need for inclusive and focused health care interventions for older adults across socioeconomic spectrum.

Objectives: Older adults in India face increased health risks due to socioeconomic and cultural characteristics found in India, including one of the highest out-of-pocket health expenditure in the world, poor quality healthcare and poor nutritional intake. In the backdrop of very little scientific data on elderly, this paper aims to provide fresh insights on the experience of multiple chronic diseases, co-morbidities and their co-variates.Study design: Cross-sectional survey studyMethods: Data from the Longitudinal Aging Study in India(LASI), Pilot survey, 2010 conducted in the four states of Karnataka, Kerala, Punjab and Rajasthan are used. Based on self reports of major chronic diseases, bi-variate analysis explores prevalence of multiple chronic disease and co-morbidities. Zero inflated Poisson regression model is estimated to assess the effects of social determinants on multiple chronic diseases. Results: Analysis reveals hypertension and diabetes as mutually critical co-morbidities of each other while heart and lung diseases are other important co-morbidities. Zero-inflated Poisson regression model estimates reveal age, education, economic status and physical activities as significant determinants of multiple chronic diseases. Conclusion: Age and social determinants show strong positive gradients of multiple chronic diseases and; considerable state variations are observed.

This article describes the prevalence of multi-morbidity and its association with self-rated and functional health using Longitudinal Aging Study in India (LASI), Pilot survey, 2010 data, on 1,683 older adults aged 45+. The prevalence of multi-morbidity is assessed as count of self-reported chronic diseases for an older adult. Limitations in activities of daily living (ADL) are used as a measure of functional health. Zero-inflated Poisson regression is estimated to examine the covariates of multi-morbidity. Moreover, logit models are used to assess the association of multi-morbidity with functional health and self-rated health. Results depict a large prevalence of multi-morbidity, limitations in ADL and poor self-rated health with pronounced state variations. Prevalence of multimorbidity was higher at higher level of education, wealth, and caste. However, educational status of older adults is seen to be negatively associated with prevalence of ADL limitations and poor self-rated health. Household wealth and caste showed no clear association with limitations in ADL and poor self-rated health. Multi-morbid older adults were found with substantially high risk of ADL limitations and poor self-rated health.

This paper aims to explore the regional disparities in the prevalence of reported morbidity in India. Using data on morbidity from the 60th round of National Sample Survey (NSS), 2004, we have calculated prevalence of individual diseases and major disease groups for India and six broad regions, namely, north, central, east, north-east, west and south. The results point to considerable regional heterogeneity both in the morbidity profile and its level. South and west regions have predominance of non-communicable diseases and functional limitations, while north and north-east regions show higher prevalence of communicable diseases. The results also point to the double burden of disease with remarkable prevalence of communicable diseases and relatively higher prevalence of non-communicable diseases, particularly among the elderly across the regions.

This article describes the prevalence of multi-morbidity and its association with self-rated and functional health using Longitudinal Aging Study in India (LASI), Pilot survey, 2010 data, on 1,683 older adults aged 45+. The prevalence of multi-morbidity is assessed as count of self-reported chronic diseases for an older adult. Limitations in activities of daily living (ADL) are used as a measure of functional health. Zero-inflated Poisson regression is estimated to examine the covariates of multi-morbidity. Moreover, logit models are used to assess the association of multi-morbidity with functional health and self-rated health. Results depict a large prevalence of multi-morbidity, limitations in ADL and poor self-rated health with pronounced state variations. Prevalence of multimorbidity was higher at higher level of education, wealth, and caste. However, educational status of older adults is seen to be negatively associated with prevalence of ADL limitations and poor self-rated health. Household wealth and caste showed no clear association with limitations in ADL and poor self-rated health. Multi-morbid older adults were found with substantially high risk of ADL limitations and poor self-rated health.