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Food and nutrition security has emerged as a primary development goal at the top of the global agenda. In 2012 the Food and Agriculture Organization (FAO) methodology was integrated into a userfriendly software named ADePT-Food Security Module (ADePT-FSM). This book aims to provide the essential guidelines of the use of ADePT-FSM and of its background methodology. It is organized into five chapters: chapter 1 introduces the background concepts of food security and food consumption data; chapter 2 describes the methodology used to derive different food security indicators; chapter 3 discusses the analysis of the derived food security statistics; chapter 4 provides guidelines on how to prepare the input datasets; and chapter 5 explains how to install and use ADePT-FSM. Over the past years, increasing attention has been paid to national household surveys by the international community in order to collect reliable and timely information on food consumption for the purpose of food security assessment. National household surveys are in fact the only available source of information to assess the distribution of food consumption within a country. ADePT-FSM aims to derive consistent and readily available food security statistics from food consumption data collected in national househoudl surveys.

Background The suspension and/or termination of many programmes funded through the United States Agency for International Development (USAID) by the new US administration has severe short- and long-term negative impacts on the health of people worldwide. We draw attention to the termination of the Demographic and Health Surveys (DHS) Program, which includes nationally representative surveys of households, DHS, Malaria Indicator Surveys [MIS]) and health facilities (Service Provision Assessments [SPA]) in over 90 low- and middle-income countries. USAID co-funding and provision of technical support for these surveys has been shut down. Main body The impact of these disruptions will reverberate across local, regional, national, and global levels and severely impact the ability to understand the levels and changes in population health outcomes and behaviours. We highlight three key impacts on (1) ongoing data collection and data processing activities; (2) future data collection and consequent lack of population-level health indicators; and (3) access to existing data and lack of support for its use. Conclusions We call for immediate action on multiple fronts. In the short term, universal access to existing data and survey materials should be restored, and surveys which were planned or in progress should be completed. In the long term, this crisis should serve as a tipping point for transforming these vital surveys. We call on national governments, regional organisations, and international partners to develop sustainable alternatives that preserve the principles (standardised questionnaires, backward compatibility, open access data with rigorous documentation) which made the DHS Program an invaluable global health resource.

Although several methods have been developed to allow for the analysis of data in the presence of missing values, no clear guide exists to help family researchers in choosing among the many options and procedures available. We delineate these options and examine the sensitivity of the findings in a regression model estimated in three random samples from the National Survey of Families and Households (n = 250-2,000). These results, combined with findings from simulation studies, are used to guide answers to a set of 10 common questions asked by researchers when selecting a missing data approach. Modern missing data techniques were found to perform better than traditional ones, but differences between the types of modern approaches had minor effects on the estimates and substantive conclusions. Our findings suggest that the researcher has considerable flexibility in selecting among modern options for handling missing data.

Household surveys are frequently used as means of vaccination coverage measurement, but obtaining accurate survey estimates present several challenges. In 2015, the World Health Organization (WHO) released a working draft of its updated Vaccination Coverage Survey Reference Manual that moved well beyond the traditional Expanded Program on Immunization (EPI) survey design. In April 2017, WHO convened a four-day meeting, to review lessons learned using the updated manual and to define an agenda for operational research about vaccination coverage surveys. About 70 stakeholders, including EPI managers and participants from 10 countries that have used the updated Survey Manual, survey experts, statisticians, partners, representatives from WHO regional offices and headquarters, and providers of technical assistance discussed methodological issues from sampling to accurately ascertaining a person’s vaccination status, optimizing data collection and data management and conducting appropriate analyses. Participants also discussed data sharing and how to best survey data for immunization decision-making. The lessons learned from the use of the updated WHO Survey Manual related mainly to operational issues to implement better quality vaccination coverage surveys. It resulted in a list of 23 recommendations for WHO, donors and partners, immunization programs, and household surveys that collect immunization data. Similarly, 14 research topics, categorized in six themes (overall survey conduction, sampling, vaccination ascertainment, data collection, data analysis and use, and inclusion of questions on knowledge, attitudes and practices) were prioritized. Top areas of further work included improving our understanding of the accuracy of caregiver recall when documented evidence of vaccination is not available, improving engagement and coordination between immunization programs and entities conducting multi-purpose household surveys such as Demographic and Health Survey and Multiple Cluster Indicator Survey, improving mechanisms for sharing vaccination survey datasets and documentation, and making better use of survey results to translate data into knowledge for decision-making. This manuscript summarizes the meeting proceedings and provides an update of actions taken by WHO since this meeting.

Data System. Federal health surveys, like the National Health Interview Survey (NHIS), represent important surveillance mechanisms for collecting timely, representative data that can be used to monitor the health and health care of the US population. Data Collection/Processing. Conducted by the National Center for Health Statistics (NCHS), NHIS uses an address-based, complex clustered sample of housing units, yielding data representative of the civilian noninstitutionalized US population. Survey redesigns that reduce survey length and eliminate proxy reporting may reduce respondent burden and increase participation. Such were goals in 2019, when NCHS implemented a redesigned NHIS questionnaire that also focused on topics most relevant and appropriate for surveillance of child and adult health. Data Analysis/Dissemination. Public-use microdata files and selected health estimates and detailed documentation are released online annually. Public Health Implications. Declining response rates may lead to biased estimates and weaken users’ ability to make valid conclusions from the data, hindering public health efforts. The 2019 NHIS questionnaire redesign was associated with improvements in the survey’s response rate, declines in respondent burden, and increases in data quality and survey relevancy. (Am J Public Health. 2023;113(4):408–415. https://doi.org/10.2105/AJPH.2022.307197 )

Background Worldwide rising cesarean section (CS) births is an issue of concern. In India, with increase in institutional deliveries there has also been an increase in cesarean section births. Aim of the study is to quantify the prevalence of cesarean section births in public and private health facility, and also to determine the factors associated with cesarean section births. Methods We analyzed data from district level household survey data 4 (DLHS-4) combined individual level dataset for 19 states/UTs of India comprising 24,398 deliveries resulting in 22,111 live births for year 2011. The percentages and Chi-square has been computed for the select variables viz. Socio demographic, maternal, antenatal care and delivery related based on type of births (CS Vs normal births). The multiple logistic regression model has been used to identify the potential risk factors associated with CS births. Results Of 22,111 live birth analyzed 49.2% were delivered at public sector, 31.9% at private sector and 18.9% were home deliveries. Prevalence of CS births were 13.7% (95% CI; 13.0- 14.3%) and 37.9% (95% CI; 36.7- 39.0%) in the public and private sectors, respectively. Higher odds of CS births were observed with- delivery at private health facility (OR 3.79; 95% C.I 3.06-4.72), urban residence (OR 1.15; 95% C.I 1.00- 1.35), first delivery after 35 years of maternal age (OR 5.5; 95% C.I 1.85- 16.4), hypertension in pregnancy (OR 1.32; 95% C.I 1.06- 1.65) and breach presentation (OR 2.37; 95% C.I. 1.63- 3.43). Conclusions Our findings shows that CS births are nearly three times more in private as compared to public sector health facilities.The higher rates of CS births, especially in private sector, not only increase the cost of care but may pose unnecessary risks to women (when there is no indications for CS). The government of India need to take measures to strengthen existing public health facilities as well as ensure that cesarean sections are performed based upon medical indications in both public and private sector health facilities.

ObjectiveTo compare the country-level absolute and relative contributions of physical activity at work and in the household, for travel, and during leisure-time to total moderate-to-vigorous physical activity (MVPA).MethodsWe used data collected between 2002 and 2019 from 327 789 participants across 104 countries and territories (n=24 low, n=34 lower-middle, n=30 upper-middle, n=16 high-income) from all six World Health Organization (WHO) regions. We calculated mean min/week of work/household, travel and leisure MVPA and compared their relative contributions to total MVPA using Global Physical Activity Questionnaire data. We compared patterns by country, sex and age group (25–44 and 45–64 years).ResultsMean MVPA in work/household, travel and leisure domains across the 104 countries was 950 (IQR 618–1198), 327 (190–405) and 104 (51–131) min/week, respectively. Corresponding relative contributions to total MVPA were 52% (IQR 44%–63%), 36% (25%–45%) and 12% (4%–15%), respectively. Work/household was the highest contributor in 80 countries; travel in 23; leisure in just one. In both absolute and relative terms, low-income countries tended to show higher work/household (1233 min/week, 57%) and lower leisure MVPA levels (72 min/week, 4%). Travel MVPA duration was higher in low-income countries but there was no obvious pattern in the relative contributions. Women tended to have relatively less work/household and more travel MVPA; age groups were generally similar.ConclusionIn the largest domain-specific physical activity study to date, we found considerable country-level variation in how MVPA is accumulated. Such information is essential to inform national and global policy and future investments to provide opportunities to be active, accounting for country context.

To describe out-of-home consumption according to the purpose and extent of industrial processing and also evaluate the association between eating out and ultra-processed food consumption, taking account of variance within and between individuals. Cross-sectional study. Brazil. The study was based on the Individual Food Intake of the Brazilian Household Budget Survey, carried out with 34 003 individuals aged 10 years or more, between May 2008 and May 2009. All food items were classified according to food processing level. The habit of eating out was evaluated through the frequency of days each individual reported eating out, described according to sociodemographic characteristics. The contribution of food energy per group and subgroup was estimated according to the frequency of eating out. In addition, multilevel modelling was employed to evaluate the association between eating out and ultra-processed food consumption. In Brazil, culinary preparations accounted for most of the energy eaten out. However, it was possible to observe a higher contribution of ultra-processed foods, especially sugary beverages and ready-to-eat meals, as the frequency of out-of-home consumption increased. Compared with food consumption exclusively at home, eating out increased the consumption of ultra-processed foods by 0·41 percentage points within and between individuals. In Brazil, the same individual and different individuals had greater consumption of ultra-processed foods when they ate out of home compared with when they ate at home. So, it is necessary to implement public policies which discourage the out-of-home consumption of ultra-processed foods and that provide affordable and accessible less-processed food options.

Background The 2019 EAT-Lancet Commission report recommends healthy diets that can feed 10 billion people by 2050 from environmentally sustainable food systems. This study compares food consumption patterns in India, from different income groups, regions and sectors (rural/urban), with the EAT-Lancet reference diet and highlights the deviations. Methods The analysis was done using data from the Consumption Expenditure Survey (CES) of a nationally representative sample of 0.102 million households from 7469 villages and 5268 urban blocks of India conducted by the National Sample Survey Organization (NSSO) in 2011–12. This is the most recent nationally representative data on household consumption in India. Calorie consumption (kcal/capita/day) of each food group was calculated using the quantity of consumption from the data and nutritional values of food items provided by NSSO. Diets for rural and urban, poor and rich households across different regions were compared with EAT-Lancet reference diet. Results The average daily calorie consumption in India is below the recommended 2503 kcal/capita/day across all groups compared, except for the richest 5% of the population. Calorie share of whole grains is significantly higher than the EAT-Lancet recommendations while those of fruits, vegetables, legumes, meat, fish and eggs are significantly lower. The share of calories from protein sources is only 6–8% in India compared to 29% in the reference diet. The imbalance is highest for the households in the lowest decile of consumption expenditure, but even the richest households in India do not consume adequate amounts of fruits, vegetables and non-cereal proteins in their diets. An average Indian household consumes more calories from processed foods than fruits. Conclusions Indian diets, across states and income groups, are unhealthy. Indians also consume excess amounts of cereals and not enough proteins, fruits, and vegetables. Importantly, unlike many countries, excess consumption of animal protein is not a problem in India. Indian policymakers need to accelerate food-system-wide efforts to make healthier and sustainable diets more affordable, accessible and acceptable.