Abstract
Background
Alcohol use contributes to 5.3% of global deaths and poses significant health risks to youth. Despite various regulatory measures by the authorities, alcohol remains a major public health concern in India.
Objective
To examine the prevalence and patterns of alcohol consumption among Indian youth aged 15–24 years and identify factors associated with its use.
Methods
Analysis of data from the National Family Health Survey-5 (2019–21), involving 30,769 male and 241,983 female youth respondents aged 15–24 years.
Results
Ever use of alcohol was reported by 10.9% of males and 0.3% of females. Among all regions northeast region demonstrated increased odds of having ever use among both males [AOR: 2.7 (1.86–-3.88)] and females [AOR: 9.5 (6.91–11.5)], and married respondents were consuming more alcohol, males [AOR: 1.5 (1.14–2.10)] and females [AOR: 3.4 (2.72–4.19)].
Conclusion
Although youth alcohol consumption has decreased from NFHS-4 to NFHS-5, it still remains a concerning issue. But the continued variance in prevalence of regions calls for a unified national policy on alcohol. Targeted, region-specific strategies are needed to reduce youth alcohol use effectively. (Data were taken for NFHS-5 India 2019–21 from the Demographic and Health Survey website).
Keywords: Alcohol consumption, Indian youth, NFHS-5, drinking patterns, secondary data
Introduction
World Health Organization (WHO) reports three million deaths every year globally due to the harmful use of alcohol, which represents 5.3% of all deaths (World Health Organization, 2022). Overall, 5.1% of the global burden of disease and injury is attributable to alcohol, in terms of disability-adjusted life years (DALYs) (Rumgay et al., 2021; World Health Organization, 2022). In the age group of 10 to 24 years, alcohol-related harm ranks as the second leading cause of DALYs, underscoring its substantial impact on the health and well-being of adolescents and young adults according to the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 (Abbafati et al., 2020; Athauda et al., 2020).
A multilevel analysis of adults aged 18 and older in 23 countries found significant regional variations in risky drinking, especially in low- and middle-income countries (LMIC), likely due to cultural and demographic factors (Grittner et al., 2020). An analysis of gender differences and regional variations in alcohol consumption in India showed a notable rise from 1998 to 2005, followed by a decline in subsequent years (Shaikh & Khan, 2021; Balasubramani et al., 2021). From 2005–06 to 2015–16, problematic drinking increased by 43.6% among men, while women experienced an 8.5% decrease (Shaikh & Khan, 2021; Balasubramani et al., 2021).
Among Indian youth, the type and frequency of alcohol consumption vary significantly by age, gender, place of residence, and region, with urban areas favoring commercial drinks like beer and wine, rural areas showing higher use of traditional liquors, and higher prevalence observed among older adolescents and those influenced by family and peers (Gupta & Hameed, 2024; Singh & Kumar, 2022). Social and cultural factors, including peer influence, play a significant role in shaping alcohol consumption patterns (Brooks-Russell et al., 2014; Gilbertson et al., 2008). Individuals are more likely to drink if alcohol use is normalized or encouraged within their social circles, with peer pressure and group norms directly increasing both the likelihood and frequency of drinking, especially among adolescents and young adults (Thakkar & Deb, 2022). Broader social factors such as family dynamics, socioeconomic status, and exposure to disadvantage or discrimination also influence drinking behaviors and risks associated with alcohol use (Collins, 2016; Sudhinaraset et al., 2016).
Alcohol consumption among adolescents and youth leads to various negative consequences, including road accidents, violence, mental health issues, self-harm, suicide attempts, and a higher risk of infectious diseases like HIV (Chowdhury & Chakraborty, 2017; Richter et al., 2016). It also results in poor academic performance, an increased likelihood of dropping out of school, and limited future job opportunities (Hall et al., 2016). Underage drinking in India displays striking heterogeneity, with Northeast India especially states like Arunachal Pradesh showing much higher prevalence and unique socio-demographic risk profiles compared to the national average (Tikhute et al., 2025; Balasubramani et al., 2021).
Alcohol use, indicated by consistent current drinking, varies significantly across different regions of India and is most common in the country’s northeastern, eastern, and northern regions (International Institute for Population Sciences, 2021). A study conducted across five states in India reveals that over one-third of the sample were current drinkers. Additionally, higher income and urban residence were positively linked to current alcohol use (Kumar et al., 2018).
Given the fact that problematic drinking is increasing over the years, the study aims to determine the regional prevalence, factors and patterns in terms of frequency and types of alcohol consumption among Indian youth aged 15 to 24 years. The study seeks to answer, “what are the prevalence estimates, pattern, and socio-demographic predictors of alcohol use among youth in India? There is limited comprehensive and contemporary evidence on the prevalence, patterns, and socio-demographic determinants of alcohol use among Indian youth aged 15–24 years, highlighting a critical gap in understanding factors driving rising problematic drinking in this population. By identifying key factors associated with alcohol use among the youth age group, the research seeks to inform public health strategies to address the issues related to alcohol consumption among young people in India.
Materials and methods
The survey datasets from the National Family Health Survey 2019–21 (NFHS-5) (International Institute for Population Sciences, 2021) was obtained from the Demographic and Health Survey organization. From the dataset, the variables with respect to age in 5-year groups, place of residence, educational level, religion, employment, social category, marital status, region, wealth index and tobacco use were selected. Sampling weights were adjusted during the analysis to correct for unequal probabilities of participant selection (Bell et al., 2012). The sample design and clustering effects were addressed using sample weights, ensuring that the complex survey structure was appropriately accounted in the statistical modeling.
As per the international standards, individuals aged 15–24 were classified as youth (United Nations, n.d.). The NFHS-5 survey gathered data from 724,115 women and 101,839 men. The current study included a sample of 30,769 men and 241,983 women aged 15 to 24 years, representing the youth population. Table 1 States and Union Territories (UTs) were categorized into North, South, East, West, Northeast, and Central India (International Institute for Population Sciences, 2021).
Table 1. States and UTs region-wise categorization.
| North | East | Northeast | Central | West | South |
|---|---|---|---|---|---|
| Chandigarh, Delhi, Haryana, Himachal Pradesh, Jammu & Kashmir, Ladakh, Punjab, Rajasthan Uttarakhand | Bihar, Jharkhand, Odisha West Bengal | Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim Tripura | Chhattisgarh, Madhya Pradesh, Uttar Pradesh | Dadra & Nagar Haveli, Daman & Diu, Goa, Gujarat, Maharashtra | Andaman & Nicobar Islands, Andhra Pradesh, Karnataka, Kerala, Lakshadweep, Puducherry, Tamil Nadu, Telangana |
Dependent variables
The main outcome of interest in this study is the use of alcohol by the youth. This was based on the question “Do you drink alcohol?” those who said “Yes” were considered ever users and those who said “No” were never users. “How often do you drink alcohol?” responses were categorized as “almost every day,” “about once a week” or “less than once a week” and “none” participants were classified as Regular Drinkers, Moderate Drinkers, Occasional Drinkers & Non-Drinkers, respectively. Preference for “Type of drink” was recorded, and the response was categorized as hard liquor, tadi madi, country liquor, wine, beer, and others. Hard liquor includes strong distilled spirits such as whiskey, rum, and vodka. Tadi/Madi refers to traditional fermented drinks made from palm or coconut sap. Country liquor consists of locally brewed alcoholic beverages.
Independent variables
Socio-demographic indicators such as age in 5-year groups, place of residence, educational level, religion, employment, social category, marital status, region, wealth index and tobacco use were considered for analysis. After conducting an in-depth review of existing literature, we carefully selected the independent variables for our study.
Data analysis
Descriptive statistics summarized socio-demographic data. Logistic regression analyzed associations between alcohol use and socio-demographic factors. Unadjusted odds identified significant predictors (p < 0.05) across demographic, social, and economic groups for inclusion in the final model. Results are reported as odds ratios with p-values and 95% confidence intervals.
Results
Of the total 272,752 youths aged 15–24 years, 30,769 (11.2%) were males and 241,983 (88.8%) were females as described in Table 2. Most respondents were from rural areas (70.1%), had an educational level of up to secondary (68.4%), belonged to the Hindu religion (80%) and 66.4% were unmarried. Among respondents, 71.3% were unemployed, reflecting limited engagement in formal work during education in India. Other Backward Class (43.3%) social category contributed for almost half respondents. Eastern region had the highest number of respondents (30.2%). Though there was a similar distribution in all classes of wealth, the poorer category had the highest proportion of respondents, 59,301 (22%).
Table 2. Frequency and percentage distribution of male & female youth by socio-demographic characteristics National Family Health Survey (NFHS)−5(2019−21).
| Socio-demographic characteristics | Male (%) N = 30,769 (11.2%) |
Female (%) N = 241,983 (88.8%) |
Total (%) N = 272,752 (100%) |
|---|---|---|---|
| Age group | |||
| 15–19 | 16,385 (53.3) | 1,22,544 (50.6) | 1,38,929 (50.9) |
| 20–24 | 14,384 (46.7) | 1,19,440 (49.4) | 1,33,824 (49.1) |
| Place of Residence | |||
| Urban | 10,538 (34.2) | 71,098 (29.4) | 81,636 (29.9) |
| Rural | 20,231 (65.8) | 170,885 (70.6) | 191,116 (70.1) |
| Educational Level | |||
| No Education | 1,386 (4.5) | 15,764 (6.5) | 17,150 (6.3) |
| Primary | 1,880 (6.1) | 15,077 (6.2) | 16,957 (6.2) |
| Secondary | 21,349 (69.4) | 165,123 (68.2) | 186,472 (68.4) |
| Higher | 6,155 (20) | 46,019 (19) | 52,174 (19.1) |
| Religion | |||
| Hindus | 23,910 (77.7) | 194,339 (80.3) | 218,249 (80) |
| Muslims | 5,365 (17.4) | 36,882 (15.2) | 42,246 (15.5) |
| Others* | 1,494 (4.9) | 10,739 (4.4) | 12,233 (4.5) |
| Employment** | |||
| Unemployed | 17,298 (71.3) | – | 17,298 (71.3) |
| Employed | 6959 (28.7) | – | 6959 (28.7) |
| Social Category | |||
| Scheduled Caste | 6,108 (21.4) | 55,474 (22.9) | 61,581 (22.6) |
| Scheduled Tribe | 2,861 (10) | 23,285 (9.6) | 26,147 (9.6) |
| Other Backward Class | 13,257 (46.5) | 105,027 (43.4) | 118,284 (43.4) |
| Others | 6,087 (21.4) | 45,421 (18.8) | 51,507 (18.9) |
| Don’t Know | 176 (0.6) | 1,544 (0.6) | 1,720 (0.6) |
| Marital Status | |||
| Never Married | 27,478 (89.3) | 153,739 (63.5) | 181,218 (66.4) |
| Married | 3,291 (10.7) | 88,244 (36.5) | 91,535 (33.6) |
| Region | |||
| North | 2,812 (9.1) | 34,528 (14.3) | 37,340 (13.7) |
| Central | 3,921 (12.7) | 53,719 (22.2) | 57,640 (21.1) |
| East | 8,330 (27.1) | 74,177 (30.7) | 82,507 (30.2) |
| North-east | 1,525 (5) | 8,545 (3.5) | 10,069 (3.7) |
| West | 7,473 (24.3) | 30,557 (12.6) | 38,030 (13.9) |
| South | 6,709 (21.8) | 40,458 (16.7) | 47,167 (17.3) |
| Wealth Index (units) | |||
| Poorest | 5,661 (18.4) | 48,714 (20.1) | 54,375 (20) |
| Poorer | 6,536 (21.2) | 52,765 (21.8) | 59,301 (22) |
| Middle | 6,509 (21.2) | 50,831 (21) | 57,340 (21) |
| Richer | 6,109 (19.8) | 48,409 (20) | 54,511 (20) |
| Richest | 5,961 (19.4) | 41,264 (17.1) | 47,225 (17) |
| Alcohol Consumption | |||
| No | 27,403 (89.1) | 241,257 (99.7) | 268,660 (98.5) |
| Yes | 3,366 (10.9) | 727 (0.3) | 4,093 (1.5) |
| Tobacco Use | |||
| Never User | 27,587 (89.7) | 241,329 (99.7) | 268,917 (98.6) |
| User | 3,182 (10.3) | 654 (0.3) | 3,836 (1.4) |
Others- Christian, Sikh, Buddhist/Neo-Buddhist, Jain, Jewish, No religion.
Data was available for only 24,257 participants.
Ever alcohol use among youth was reported by 3366 (10.9%) males and 727 (0.3%) females. At the same time, tobacco use among youth was reported by 3182 (10.3%) and 654 (0.3%) of males and females, respectively.
Youth aged 20–24 years were more likely to be ever users than those aged 15–19 years for both genders, with males [AOR: 3.0 (2.43–3.81)] and females [AOR: 1.8 (1.53–2.27)] as reported in Table 3. Youth from the northeast region demonstrated increased odds of having ever use compared to other regions, among both males [AOR: 2.7 (1.86–3.88)] and females [AOR: 9.5 (6.91–11.5)], with those from south region followed the trend. Uneducated females reported a higher likelihood of alcohol use compared to educated ones [AOR: 2.9 (2.35–3.68)]. Married respondents were consuming more alcohol, males [AOR: 1.5 (1.14–2.10)] and females [AOR: 3.4 (2.72 – 4.19)]. Tobacco usage was significantly associated with alcohol consumption in males [AOR: 5.1 (3.89–6.73)] and females [AOR: 4.46 (2.96–6.73)]. Women belonging to the richest wealth class [AOR: 1.16 (0.82–1.64)] had highest odds of ever alcohol use.
Table 3. Socio-demographic determinants of alcohol use among male youth (n = 30,769), in India female youth (n = 241,983), in India.
| Characteristics | Males (n = 30,769) | Females (n = 241,983) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| n (%) | Ever Users (%) | Crude OR (95% CI) | P-value | Adjusted OR (95% CI) | P-value | n (%) | Ever Users (%) | Crude OR (95% CI) | P value | Adjusted OR (95% CI) | P - value | |
| Age | ||||||||||||
| 15–19 | 16,385 (53.3) | 943 (28) | 1 | <0.001 | 1 | <0.001 | 1,22,544 (50.6) | 238 (32) | 1 | <0.001 | 1 | <0.001 |
| 20–24 | 14,384 (46.7) | 2423 (72) | 3.3 (2.88–3.81) | 3.0 (2.43–3.81) | 1,19,440 (49.4) | 489 (68) | 2.1 (1.75–2.54) | 1.8 (1.53–2.27) | ||||
| Locality | ||||||||||||
| Urban | 10,538 (34) | 1153 (34) | 1 | 0.997 | 71,097 (29) | 273 (38) | 1 | 0.213 | ||||
| Rural | 20,231 (66) | 2213 (66) | 1.2 (0.95–1.42) | 170,885 (71) | 489 (67) | 0.8 (0.67–1.09) | ||||||
| Religion | ||||||||||||
| Hindu | 23,910 (78) | 2922 (87) | 1 | <0.001 | 1 | <0.001 | 194,339 (80) | 605 (83) | 1 | <0.001 | 1 | <0.001 |
| Muslim | 5365 (17) | 233 (7) | 0.3 (0.25–0.43) | 0.1 (0.11–0.32) | 36,882 (15) | 9 (1) | 0.07 (0.03–0.17) | 0.6 (0.02–0.12) | ||||
| Others* | 1494 (5) | 211 (6) | 1.2 (0.92–1.49) | 1.21 (0.84–1.75) | 10,739 (4) | 113 (16) | 3.4 (2.56–4.49) | 1.73 (1.23–2.42) | ||||
| Region | ||||||||||||
| North | 2811 (9) | 202 (6) | 1 | <0.001 | 1 | <0.001 | 48,694 (20) | 89 (12) | 1 | <0.001 | 1 | <0.001 |
| Centre | 3920 (13) | 317 (9) | 1.1 (0.96–1.34) | 0.93 (0.69–1.23) | 47,193 (20) | 49 (7) | 0.3 (0.25–0.50) | 0.43 (0.29–0.61) | ||||
| East | 8329 (27) | 1174 (35) | 2.1 (1.75–2.57) | 2.1 (1.55–2.77) | 60,206 (25) | 243 (33) | 1.2 (0.93–1.71) | 1.34 (0.94-1.92) | ||||
| North-east | 1524 (5) | 220 (7) | 2.2 (1.76–2.72) | 2.7 (1.86–3.88) | 31,970 (13) | 176 (24) | 8.1 (6.16–10.74) | 9.5 (6.91–1.15) | ||||
| West | 7473 (24) | 437 (13) | 0.8 (0.54–1.19) | 0.39 (0.18–0.82) | 22,023 (9) | 38 (5) | 0.5 (0.23–0.99) | 0.54 (0.26–1.15) | ||||
| South | 6709 (22) | 1016 (30) | 2.3 (1.87–2.84) | 2.6 (1.95–3.58) | 31,094 (13) | 130 (18) | 1.2 (0.91–1.70) | 1.57 (1.14–2.15) | ||||
| Education level | ||||||||||||
| Has education | 29,384 (96) | 3158 (94) | 1 | 0.01 | 1 | 0.789 | 15,077 (6) | 62 (9) | 1 | <0.001 | 1 | <0.001 |
| No education | 1386 (5) | 208 (6) | 1.4 (1.08–1.99) | 0.9 (0.53–1.60) | 15,764 (7) | 136 (19) | 3.3 (2.66–4.14) | 2.9 (2.35–3.68) | ||||
| Marital Status | ||||||||||||
| Unmarried | 3226 (11) | 750 (22) | 1 | <0.001 | 1 | 0.01 | 153,739 (64) | 409 (56) | 1 | 0.001 | 1 | <0.001 |
| Married | 27,478 (89) | 2615 (78) | 2.7 (2.34–3.25) | 1.5 (1.14–2.10) | 88,244 (36) | 317 (44) | 1.35 (1.13–1.62) | 3.4 (2.72–4.19) | ||||
| Tobacco Use | ||||||||||||
| Non-user | 27,587 (90) | 2520 (75) | 1 | <0.001 | 1 | <0.001 | 241,329 (100) | 690 (95) | 1 | <0.001 | 1 | <0.001 |
| User | 3181 (10) | 846 (25) | 3.6 (3.07–4.22) | 5.1 (3.89–6.73) | 654 (0.1) | 36 (5) | 20.5 (13.99–29.96) | 4.46 (2.96–6.73) | ||||
| Wealth Index | ||||||||||||
| Poorest | 1600 (18) | 705 (21) | 1 | 0.112 | 48,714 (20) | 276 (38) | 1 | <0.001 | 1 | <0.001 | ||
| Poorer | 1924 (21) | 748 (22) | 0.9 (0.76–1.08) | 52,765 (22) | 116 (16) | 0.3 (0.31–0.49) | 0.4 (0.36–0.57) | |||||
| Middle | 1970 (22) | 736 (21) | 0.9 (0.74–1.08) | 50,831 (21) | 80 (11) | 0.2 (0.20–0.37) | 0.3 (0.27–0.50) | |||||
| Richer | 1795 (20) | 675 (20) | 0.9 (0.68–1.12) | 48,409 (20) | 91 (12) | 0.3 (0.25–0.44) | 0.5 (0.37–0.69) | |||||
| Richest | 1864 (20) | 501 (15) | 0.6 (0.47–0.88) | 41,264 (17) | 161 (22) | 0.6 (0.51–0.93) | 1.16 (0.82–1.64) | |||||
| Employment status | ||||||||||||
| Unemployed youth | 4700 (51) | 484 (54) | 1 | 0.01 | 1 | 0.51 | ||||||
| Professional/technical/ managerial |
269 (3) | 24 (3) | 1.1 (0.68–1.67) |
0. (0.36–2.03) |
||||||||
| Clerical youth/Sales/Services & domestic |
931 (10) | 101 (11) | 1.0 (0.87–1.19) |
1.1 (0.71–1.58) |
||||||||
| Agricultural youth |
1594 (17) | 129 (14) | 0.80 (0.70–0.91) |
0.8 (0.54–1.14) |
||||||||
| Skilled/unskilled/manual | 1660 (18) | 155 (17) | 0.951 (0.82–1.09) |
0.8 (0.58–1.11) |
||||||||
Notes: 1(Ref) = Reference Category, OR = Odds Ratio, CI = Confidence Interval.
Figure 1 shows the frequency of drinking among youth. Regular drinkers comprised a small proportion both among the male and females. Female youth were found to have lower rates of alcohol consumption across all categories compared to males.
Figure 1. Frequency of alcohol consumption in youth.
Figure 2 presents the percentage distribution of male and female youth consuming different alcoholic beverages. Beer consumption was the most reported among men (43%), followed by hard liquor (18.5%) and country liquor (12.7%). Among females, beer (31%) and Tadi Madi (29%) were reported to be equally popular.
Figure 2. Type of liquor consumed by male & female youth.
Discussion
The current study investigated socio-demographic patterns of alcohol consumption among youth. The current study found that 10.9% of males used alcohol, while only 0.3% of females reported consuming it. Notably, the prevalence among male youth decreased from 16.1% in NFHS-4 (2015–16) to 10.9% in NFHS-5 (2019–21), and among female youth from 0.6% to 0.3% during the same period (NFHS-4, 2015–16; NFHS-5, 2019–21; Jaisoorya et al., 2018; Manimunda et al., 2017; Ganesh Kumar et al., n.d.). A Ministry of Social Welfare and Justice survey found that 27.3% of men over 18 consume alcohol, compared to just 1.6% of women (Ambekar et al., 2019).
While survey data show a decline in prevalence, sales and overall consumption of alcohol in India have increased, as reported by the Confederation of Indian Alcoholic Beverage Companies (CIABC) and the World Health Organization (Hammer et al., 2018; Jaipuria, 2023). India is the third-largest alcoholic beverage market, with an annual volume of over 970 crore liters valued at ₹4.5 trillion (Jaipuria, 2023). Between 2000 and 2018, per capita annual alcohol consumption rose from 2.3 L to 5.5 L, driven by population growth, urbanization, and rising disposable incomes, especially among the middle class (Rastogi et al., 2022).
Socioeconomic factors play a significant role in alcohol consumption patterns. Lower income, manual labor occupations, and lower educational attainment are associated with higher alcohol use, particularly in rural and tribal populations (Keyes et al., 2008). Cultural dynamics in India significantly limit women’s alcohol consumption, reflecting societal values (Parry, 2007) and the same is observed in the present study also. The observed pattern in this study shows higher alcohol use among males, notable urban residence differences, a strong link between alcohol and tobacco use, and associations with socioeconomic status. These findings align with recent literature on the nature and distribution of alcohol consumption and the epidemiology of alcohol use in India, further substantiating established trends in the field (Balasubramani et al., 2021; Singh & Kumar, 2022).
Alcohol consumption in India is often underreported due to cultural stigmas and social norms against discussing drinking habits, especially in rural areas where traditional values prevail (Dutta et al., 2014). A study in Sikkim found widespread consumption of unrecorded alcohol and highlighted significant alcohol-related issues, indicating a need for policy changes on its production and sale (Chakrabarti et al., 2015). A significant portion of alcohol consumption in India involves unrecorded or illicit alcohol, which is not captured in official statistics. This includes home-brewed drinks like chang and raksi, which are culturally ingrained and widely consumed in certain regions (Chakrabarti et al., 2015). The present study having a cross-sectional design has inherent limitations wherein causality cannot be established and warrants need for longitudinal studies. In addition, interviewer-administered questionnaires are subjected to misreporting, social desirability bias, and recall bias. These factors could have led to an underestimation of the actual prevalence of alcohol use in the present study.
The present study reveals the prevalence and patterns of alcohol use among youth in India. Though the prevalence was found to be decreasing, a considerable number of male youths are found to be ever alcohol users. This calls for designing targeted interventions that are more focused on men. Additionally, the study found a strong association between alcohol consumption and tobacco use. Thus, there is a need for appropriate intervention like early or community interventions for youth to mitigate the harm caused by substance use. These epidemiological consistencies underscore an urgent need to situate youth-focused prevention within a coordinated national alcohol control strategy. India currently lacks a unified national alcohol policy and state responses remain heterogeneous, limiting the impact of these policies (Schess et al., 2023). Considering these findings, it is crucial to include more practical recommendations to better tackle the increasing alcohol consumption among young people in India. This includes implementing educational institution – based prevention programs that promote awareness and early behavioral change in the Northeast region. Implementation of community action projects that mobilize local leadership, enforce laws, and use media campaigns to raise awareness about harms due to alcohol can be prioritized.
Acknowledgments
We would like to thank the Demographic Health Survey program for giving permission to use the NFHS-5 datasets.
Funding
This work was supported by Dr. TMA Pai Scholarship provided by Manipal Academy of Higher Education, Manipal. Dr. Upendra Bhojani is supported for his time through the Wellcome Trust DBT India Alliance [IA/CPH/22/1/506533, IA/CRC/20/1/600007].
Footnotes
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The data that support the findings of this study are openly available in “The Demographic and Health Surveys (DHS) Program” at https://dhsprogram.com/methodology/survey/survey-display-541.cfm, reference number [IAMR7ESV.ZIP; IAIR7ESV.ZIP].
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are openly available in “The Demographic and Health Surveys (DHS) Program” at https://dhsprogram.com/methodology/survey/survey-display-541.cfm, reference number [IAMR7ESV.ZIP; IAIR7ESV.ZIP].