Biomedical subjects
Neeraj Dhingra
Publications and source records attributed to Neeraj Dhingra.
Trends in HIV-1 in young adults in south India from 2000 to 2004: a prevalence study.
BACKGROUND: Major increases in HIV-1 prevalence in India have been predicted. Incident infections need to be tracked to understand the epidemic's course, especially in some southern states of India where the epidemic is more advanced. To estimate incidence, we investigated the prevalence of HIV-1 in young people attending antenatal and sexually transmitted infection (STI) clinics in India. METHODS: We analysed unlinked, anonymous HIV-1 prevalence data from 294 050 women attending 216 antenatal clinics and 58 790 men attending 132 STI clinics in 2000-04. Southern and northern states were analysed separately. FINDINGS: The age-standardised HIV-1 prevalence in women aged 15-24 years in southern states fell from 1.7% to 1.1% in 2000-04 (relative reduction 35%; p(trend)<0.0001, yearly reduction 11%), but did not fall significantly in women aged 25-34 years. Reductions in women aged 15-24 years were seen in key demographic groups and were similar in sites tested continuously or in all sites. Prevalence in the north was about a fifth of that in the south, with no significant decreases (or increases) in 2000-04. Prevalence fell in men aged 20-29 years attending STI clinics in the south (p(trend)<0.0001), including those with ulcerative STIs (p(trend)=0.0008), but reductions were more modest in their northern counterparts. INTERPRETATION: A reduction of more than a third in HIV-1 prevalence in 2000-04 in young women in south India seems realistic, and is not easily attributable to bias or to mortality. This fall is probably due to rising condom use by men and female sex workers in south India, and thus reduced transmission to wives. Expansion of peer-based condom and education programmes for sex workers remains a top priority to control HIV-1 in India.
Low female[corrected]-to-male [corrected] sex ratio of children born in India: national survey of 1.1 million households.
BACKGROUND: Fewer girls than boys are born in India. Various hypotheses have been proposed to explain this low sex ratio. Our aim was to ascertain the contribution of prenatal sex determination and selective abortion as measured by previous birth sex. METHODS: We analysed data obtained for the Special Fertility and Mortality Survey undertaken in 1998. Ever-married women living in 1.1 million households in 6671 nationally-representative units were asked questions about their fertility history and children born in 1997. FINDINGS: For the 133 738 births studied for 1997, the adjusted sex ratio for the second birth when the preceding child was a girl was 759 per 1000 males (99% CI 731-787). The adjusted sex ratio for the third child was 719 (675-762) if the previous two children were girls. By contrast, adjusted sex ratios for second or third births if the previous children were boys were about equal (1102 and 1176, respectively). Mothers with grade 10 or higher education had a significantly lower adjusted sex ratio (683, 610-756) than did illiterate mothers (869, 820-917). Stillbirths and neonatal deaths were more commonly male, and the numbers of stillbirths were fewer than the numbers of missing births, suggesting that female infanticide does not account for the difference. INTERPRETATION: Prenatal sex determination followed by selective abortion of female fetuses is the most plausible explanation for the low sex ratio at birth in India. Women most clearly at risk are those who already have one or two female children. Based on conservative assumptions, the practice accounts for about 0.5 million missing female births yearly, translating over the past 2 decades into the abortion of some 10 million female fetuses.
Prospective study of one million deaths in India: rationale, design, and validation results.
BACKGROUND: Over 75% of the annual estimated 9.5 million deaths in India occur in the home, and the large majority of these do not have a certified cause. India and other developing countries urgently need reliable quantification of the causes of death. They also need better epidemiological evidence about the relevance of physical (such as blood pressure and obesity), behavioral (such as smoking, alcohol, HIV-1 risk taking, and immunization history), and biological (such as blood lipids and gene polymorphisms) measurements to the development of disease in individuals or disease rates in populations. We report here on the rationale, design, and implementation of the world's largest prospective study of the causes and correlates of mortality. METHODS AND FINDINGS: We will monitor nearly 14 million people in 2.4 million nationally representative Indian households (6.3 million people in 1.1 million households in the 1998-2003 sample frame and 7.6 million people in 1.3 million households in the 2004-2014 sample frame) for vital status and, if dead, the causes of death through a well-validated verbal autopsy (VA) instrument. About 300,000 deaths from 1998-2003 and some 700,000 deaths from 2004-2014 are expected; of these about 850,000 will be coded by two physicians to provide causes of death by gender, age, socioeconomic status, and geographical region. Pilot studies will evaluate the addition of physical and biological measurements, specifically dried blood spots. Preliminary results from over 35,000 deaths suggest that VA can ascertain the leading causes of death, reduce the misclassification of causes, and derive the probable underlying cause of death when it has not been reported. VA yields broad classification of the underlying causes in about 90% of deaths before age 70. In old age, however, the proportion of classifiable deaths is lower. By tracking underlying demographic denominators, the study permits quantification of absolute mortality rates. Household case-control, proportional mortality, and nested case-control methods permit quantification of risk factors. CONCLUSIONS: This study will reliably document not only the underlying cause of child and adult deaths but also key risk factors (behavioral, physical, environmental, and eventually, genetic). It offers a globally replicable model for reliably estimating cause-specific mortality using VA and strengthens India's flagship mortality monitoring system. Despite the misclassification that is still expected, the new cause-of-death data will be substantially better than that available previously.