Burden, determinants, consequences and care of multimorbidity in rural and urbanising Telangana, India: protocol for a mixed-methods study within the APCAPS cohort.

INTRODUCTION: The epidemiological and demographic transitions are leading to a rising burden of multimorbidity (co-occurrence of two or more chronic conditions) worldwide. Evidence on the burden, determinants, consequences and care of multimorbidity in rural and urbanising India is limited, partly due to a lack of longitudinal and objectively measured data on chronic health conditions. We will conduct a mixed-methods study nested in the prospective Andhra Pradesh Children and Parents' Study (APCAPS) cohort to develop a data resource for understanding the epidemiology of multimorbidity in rural and urbanising India and developing interventions to improve the prevention and care of multimorbidity. METHODS AND ANALYSIS: We aim to recruit 2100 APCAPS cohort members aged 45+ who have clinical and lifestyle data collected during a previous cohort follow-up (2010-2012). We will screen for locally prevalent non-communicable, infectious and mental health conditions, alongside cognitive impairments, disabilities and frailty, using a combination of self-reported clinical diagnosis, symptom-based questionnaires, physical examinations and biochemical assays. We will conduct in-depth interviews with people with varying multimorbidity clusters, their informal carers and local healthcare providers. Deidentified data will be made available to external researchers. ETHICS AND DISSEMINATION: The study has received approval from the ethics committees of the National Institute of Nutrition and Indian Institute of Public Health Hyderabad, India and the London School of Hygiene and Tropical Medicine, UK. Meta-data and data collection instruments will be published on the APCAPS website alongside details of existing APCAPS data and the data access process (www.lshtm.ac.uk/research/centres-projects-groups/apcaps).

Discrimination and intimate partner violence among a sample of bisexual and gay men in the United States: a cross-sectional study.

Purpose: Intimate partner violence (IPV) is becoming more recognized as a public health concern among sexual minority men, including bisexual and gay men. Guided by the Minority Stress Model, we assessed the relationship between perceived discrimination and three forms of IPV among a sample of bisexual and gay men living in the United States. Methods: We analyzed data as part of the Men's Body Project, a cross-sectional study launched in 2020 to assess health behaviors of bisexual and gay men. Results: A total of 549 individuals participated in the survey, of which 52% were gay and 48% were bisexual men. Perceived discrimination was significantly associated with elevated odds ratios ranging from 1.15 to 1.18 across three forms of IPV, with Physical IPV odds ratio being highest. Conclusion: Given the significant association between perceived discrimination and IPV, interventions aimed at addressing IPV experiences among sexual minority men must consider the role of minority stress.

Statistical analysis plan and protocol updates for Gestational diabetes in Uganda and India: Design and Evaluation of Educational Films for Improving Screening and Self-management (GUIDES) trial.

BACKGROUND: Timely detection and management of gestational diabetes mellitus (GDM) have been identified as a high priority for policymakers in low- and middle-income countries (LMICs). The GUIDES trial will evaluate a package of three interconnected film-based interventions aimed at improving the timely detection and management of GDM. The protocol for this trial has previously been published; this publication outlines the statistical analysis plan for the trial. METHODS AND DESIGN: The GUIDES study is a multi-country cluster-randomised controlled trial consisting of one trial conducted in Uganda and one in India (30 clusters in each country). Mixed effects models will be used to compare the primary study outcomes of the proportion of women who are tested for GDM between 24 and 32 weeks of pregnancy and the mean fasting blood sugar of women with GDM at 34-week follow-up while accounting for clustering. Secondary analyses will compare the proportion of women with self-reported GDM diagnosis at 32 weeks of pregnancy and the proportion of women with adverse perinatal outcomes related to GDM up to 4 weeks after birth in each trial arm. TRIAL STATUS AND DISCUSSION: Follow-up is expected to end in March 2023 in Uganda and in May 2023 in India. Analyses will be carried out following this statistical analysis plan in the month following trial completion. TRIAL REGISTRATION: ClinicalTrials.gov NCT03937050. Registered on 3 May 2019. Clinical Trials Registry India CTRI/2020/02/023605. Registered on 26 February 2020.

Association between dating app use and unhealthy weight control behaviors and muscle enhancing behaviors in sexual minority men: a cross-sectional study.

BACKGROUND: Body image concerns are prevalent and are viewed as risk factors for engaging in unhealthy weight control behaviors (UWCBs), such as purging, fasting, and the misuse of laxatives and diet pills. Studies have also linked UWCBs to the development of eating disorders. In the United States (U.S.), sexual minority men (e.g., bisexual, gay, and men who have sex with men) are prone to UWCBs often as a result of societal pressures to achieve certain standards of appearance - of which are often perpetuated through various media platforms. A growing number of studies have explored the possible role mobile dating applications ("dating apps") play in contributing to UWCBs. To our knowledge, such studies have not explored this possible relationship between dating apps and UWCBs in sexual minority men (SMM). To fill this gap in the scientific literature, the present study assessed the association between dating app use and UWCBs and muscle enhancing behaviors among a sample of adult SMM in the U.S. METHOD: 549 SMM participated in an anonymous survey from Qualtrics Survey Panels. UWCBs and muscle enhancing behaviors were assessed through items adapted from national surveys. Body image dissatisfaction was assessed using the Male Body Attitudes Scales. Participants also reported their history of dating app use. We performed descriptive statistics, chi-square tests, and student's t-tests. Multivariable logistic regression models assessed the relationship between dating app use and UWCBs and muscle enhancing behaviors. RESULTS: Dating app users had significantly higher body image dissatisfaction scores than non-users. Dating app users also demonstrated significantly elevated odds of engaging in four UWCBs and muscle enhancing behaviors: laxatives, diet pills, muscle-building supplements, and protein powders. CONCLUSIONS: This is one of the first studies to assess dating app use and its association with UWCBs and muscle enhancing behaviors in SMM. Increased surveillance and detection for such behaviors among SMM, particularly those using dating apps, are needed.

Association between perceived discrimination and food insecurity among sexual minority men.

Background: Despite numerous studies focusing on the burden of food insecurity, few have assessed its impact among sexual minority (LGB) populations. Sexual minority individuals are subject to chronic levels of stress, including stigma, prejudice, and discrimination as a result of their sexual orientation identity. While few studies have documented food insecurity among sexual minorities, the relationship between food insecurity and discrimination among this stigmatized population remains unclear. Aim: This study aimed to assess the toll of food insecurity among a sample of sexual minority men (i.e. bisexual and gay men) in the U.S. Guided by the Minority Stress Theory, the study also assessed the relationship between food insecurity and perceived discrimination. Methods: Researchers disseminated an online survey and recruited gay and bisexual men in the U.S. The survey collected participants' demographic information, perceived discrimination, and food insecurity. Multivariable logistic regression analyses were used to examine the association between perceived discrimination and food insecurity. Results: A total of 504 sexual minority men (49.2% bisexual and 50.8% gay) completed the survey. Results from logistic regression models suggest perceived discrimination was significantly associated with food insecurity (OR = 1.14, CI: 1.11-1.18). Those living with a partner demonstrated lower odds of food insecurity (OR = 0.38, CI: 0.18-0.71). Conclusion: The present study found a significant association between perceived discrimination and food insecurity among sexual minority men. The findings need to be replicated and further explored through additional research, including qualitative methods, to better elucidate how discrimination is related to experiences with food insecurity among gay and bisexual men.

Racial/Ethnic Disparities in Food Pantry Use and Barriers in Massachusetts during the First Year of the COVID-19 Pandemic.

This study sought to describe racial disparities in food insecurity, food pantry use, and barriers to and experiences with food pantries during the first year of the COVID-19 pandemic. We surveyed 2928 adults in Massachusetts regarding food access in the year before and during the first year of the pandemic. Weighted multivariable logistic regression models assessed racial differences in barriers to and experiences with pantry use during the pandemic. Black and Latino adults experienced the highest prevalence of food insecurity and pantry use. Additionally, Black and Latino adults reported more barriers to, but less stigma around, pantry use compared to White adults. Latino adults were less likely to know about pantry hours/locations and encounter staff who spoke their language. Black and Latino adults were also more likely to find pantry hours/locations inconvenient and have difficulty with transportation. The COVID-19 pandemic resulted in increased food insecurity, and food access inequities persisted. Programmatic policies to improve pantry access in communities of color could include increasing the hours/days that pantries are open, increasing bilingual staff, providing transportation or delivery, and creating multilingual public awareness campaigns on how to locate pantries.

Diaper Need During the COVID-19 Pandemic Associated with Poverty, Food Insecurity, and Chronic Illness: An Analysis of a Representative State Sample of Caretakers with Young Children.

Objectives: Diaper need is an important form of material hardship for families with young children. This study quantified diaper need during the COVID-19 pandemic and examined factors associated with diaper need. Methods: Using a representative statewide sample of adults in Massachusetts, diaper need was assessed during the COVID-19 pandemic among respondents with at least one child 0-4 years of age in diapers (n=353). Bivariate tests examined associations between diaper need and individual and household factors. Multivariable regression was used to examine associations between diaper need and demographic factors, job loss, and mental health during the pandemic. Results: More than one in three respondents reported diaper need (36.0%). Demographic factors associated with diaper need were age <25 years, Latino ethnicity, having less than a high school degree, unemployment before the pandemic, household income <$50,000, household food insecurity, or having a household member with a chronic disease. Diaper need was higher among respondents who utilized a nutrition assistance program or a food pantry during the pandemic. In multivariable analyses considering job loss and mental health during the pandemic, diaper need was associated with household income <$50,000 (odds ratio [OR] 3.61; confidence interval [95% CI] 1.40-9.26) and a chronic disease diagnosis within the household (OR 4.26; 95% CI 1.77-10.29). Conclusions: This study indicates a level of diaper need similar to what was documented before the COVID-19 pandemic despite federal stimulus payments and increased distributions by local diaper banks. The findings identify groups at increased risk and suggest opportunities to reach those at risk through food assistance programs.

Process evaluation protocol of a cluster randomised trial for a scalable solution for delivery of Diabetes Self-Management Education in Thailand (DSME-T).

INTRODUCTION: Type 2 diabetes mellitus is a major global challenge, including for Thai policy-makers, as an estimated 4 million people in Thailand (population 68 million) have this condition. Premature death and disability due to diabetes are primarily due to complications which can be prevented by good risk factor control. Diabetes Self-Management Education (DSME) programmes provide patients with diabetes with the necessary knowledge and skills to effectively manage their disease. Currently, a trial is being conducted in Thailand to evaluate the effectiveness, defined as HbA1c<7 at 12 months after enrolment, of a culturally tailored DSME in Thailand. A process evaluation can provide further interpretation of the results from complex interventions as well as insight into the success of applying the programme into a broader context. METHODS AND ANALYSIS: The aim of the process evaluation is to understand how and why the intervention was effective or ineffective and to identify contextually relevant strategies for future successful implementation. For the process evaluation, the design will be a mixed-method study collecting data from nurse providers, and village health volunteers (community health workers) as well as patients. This will be conducted using observations, interviews and focus groups from the three purposively selected groups at the beginning and end of trial. Quantitative data will be collected through surveys conducted at the beginning, during 6-month follow-up, and at the end of trial. The mixed-methods analysis will be triangulated to assess differences and similarities across the various data sources. The overall effectiveness of the intervention will be examined using multilevel analysis of repeated measures. ETHICS AND DISSEMINATION: Study approved by the Chiang Mai University Research Ethics Committee (326/2018) and the London School of Hygiene & Tropical Medicine (16113/RR/12850). Results will be published in open access, peer-reviewed scientific journals. TRIAL REGISTRATION NUMBER: NCT03938233.

A Multi-Site Analysis of the Prevalence of Food Insecurity in the United States, before and during the COVID-19 Pandemic.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic profoundly affected food systems including food security. Understanding how the COVID-19 pandemic impacted food security is important to provide support and identify long-term impacts and needs. OBJECTIVE: The National Food Access and COVID research Team (NFACT) was formed to assess food security over different US study sites throughout the pandemic, using common instruments and measurements. This study presents results from 18 study sites across 15 states and nationally over the first year of the COVID-19 pandemic. METHODS: A validated survey instrument was developed and implemented in whole or part through an online survey of adults across the sites throughout the first year of the pandemic, representing 22 separate surveys. Sampling methods for each study site were convenience, representative, or high-risk targeted. Food security was measured using the USDA 6-item module. Food security prevalence was analyzed using ANOVA by sampling method to assess statistically significant differences. RESULTS: Respondents (n = 27,168) indicate higher prevalence of food insecurity (low or very low food security) since the COVID-19 pandemic, compared with before the pandemic. In nearly all study sites, there is a higher prevalence of food insecurity among Black, Indigenous, and People of Color (BIPOC), households with children, and those with job disruptions. The findings demonstrate lingering food insecurity, with high prevalence over time in sites with repeat cross-sectional surveys. There are no statistically significant differences between convenience and representative surveys, but a statistically higher prevalence of food insecurity among high-risk compared with convenience surveys. CONCLUSIONS: This comprehensive study demonstrates a higher prevalence of food insecurity in the first year of the COVID-19 pandemic. These impacts were prevalent for certain demographic groups, and most pronounced for surveys targeting high-risk populations. Results especially document the continued high levels of food insecurity, as well as the variability in estimates due to the survey implementation method.

Exploration of Machine Learning and Statistical Techniques in Development of a Low-Cost Screening Method Featuring the Global Diet Quality Score for Detecting Prediabetes in Rural India.

BACKGROUND: The prevalence of type 2 diabetes has increased substantially in India over the past 3 decades. Undiagnosed diabetes presents a public health challenge, especially in rural areas, where access to laboratory testing for diagnosis may not be readily available. OBJECTIVES: The present work explores the use of several machine learning and statistical methods in the development of a predictive tool to screen for prediabetes using survey data from an FFQ to compute the Global Diet Quality Score (GDQS). METHODS: The outcome variable prediabetes status (yes/no) used throughout this study was determined based upon a fasting blood glucose measurement ≥100 mg/dL. The algorithms utilized included the generalized linear model (GLM), random forest, least absolute shrinkage and selection operator (LASSO), elastic net (EN), and generalized linear mixed model (GLMM) with family unit as a (cluster) random (intercept) effect to account for intrafamily correlation. Model performance was assessed on held-out test data, and comparisons made with respect to area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. RESULTS: The GLMM, GLM, LASSO, and random forest modeling techniques each performed quite well (AUCs >0.70) and included the GDQS food groups and age, among other predictors. The fully adjusted GLMM, which included a random intercept for family unit, achieved slightly superior results (AUC of 0.72) in classifying the prediabetes outcome in these cluster-correlated data. CONCLUSIONS: The models presented in the current work show promise in identifying individuals at risk of developing diabetes, although further studies are necessary to assess other potentially impactful predictors, as well as the consistency and generalizability of model performance. In addition, future studies to examine the utility of the GDQS in screening for other noncommunicable diseases are recommended.

Validation of Global Diet Quality Score Among Nonpregnant Women of Reproductive Age in India: Findings from the Andhra Pradesh Children and Parents Study (APCAPS) and the Indian Migration Study (IMS).

BACKGROUND: In India, there is a need to monitor population-level trends in changes in diet quality in relation to both undernutrition and noncommunicable diseases. OBJECTIVES: We conducted a study to validate a novel diet quality score in southern India. METHODS: We included data from 3041 nonpregnant women of reproductive age (15-49 years) from 2 studies in India. Diet was assessed using a validated food frequency questionnaire (FFQ). The Global Diet Quality Score (GDQS) was calculated from 25 food groups (16 healthy; 9 unhealthy), with points for each group based on the frequency and quantity of items consumed in each group. We used Spearman correlations to examine correlations between the GDQS and several nutrient intakes of concern. We examined associations between the GDQS [overall, healthy (GDQS+), and unhealthy (GDQS-) submetrics] and overall nutrient adequacy, micro- and macronutrients, body mass index (BMI), midupper arm circumference, hemoglobin, blood pressure, high density lipoprotein (HDL), and total cholesterol (TC). RESULTS: The mean GDQS was 23 points (SD, 3.6; maximum, 46.5). In energy-adjusted models, positive associations were found between the overall GDQS and GDQS+ and intakes of calcium, fiber, folate, iron, monounsaturated fatty acid (MUFA), protein, polyunsaturated fatty acid (PUFA), saturated fatty acid (SFA), total fat, and zinc (ρ = 0.12-0.39; P < 0.001). Quintile analyses showed that the GDQS was associated with better nutrient adequacy. At the same time, the GDQS was associated with higher TC, lower HDL, and higher BMI. We found no associations between the GDQS and hypertension. CONCLUSIONS: The GDQS was a useful tool for reflecting overall nutrient adequacy and some lipid measures. Future studies are needed to refine the GDQS for populations who consume large amounts of unhealthy foods, like refined grains, along with healthy foods included in the GDQS.

There's an App for That: Development of an Application to Operationalize the Global Diet Quality Score.

BACKGROUND: The global diet quality score (GDQS) is a simple, standardized metric appropriate for population-based measurement of diet quality globally. OBJECTIVES: We aimed to operationalize data collection by modifying the quantity of consumption cutoffs originally developed for the GDQS food groups and to statistically evaluate the performance of the operationalized GDQS relative to the original GDQS against nutrient adequacy and noncommunicable disease (NCD)-related outcomes. METHODS: The GDQS application uses a 24-h open-recall to collect a full list of all foods consumed during the previous day or night, and automatically classifies them into corresponding GDQS food group. Respondents use a set of 10 cubes in a range of predetermined sizes to determine if the quantity consumed per GDQS food group was below, or equal to or above food group-specific cutoffs established in grams. Because there is only a total of 10 cubes but as many as 54 cutoffs for the GDQS food groups, the operationalized cutoffs differ slightly from the original GDQS cutoffs. RESULTS: A secondary analysis using 5 cross-sectional datasets comparing the GDQS with the original and operationalized cutoffs showed that the operationalized GDQS remained strongly correlated with nutrient adequacy and was equally sensitive to anthropometric and other clinical measures of NCD risk. In a secondary analysis of a longitudinal cohort study of Mexican teachers, there were no differences between the 2 modalities with the beta coefficients per 1 SD change in the original and operationalized GDQS scores being nearly identical for weight gain (-0.37 and -0.36, respectively, P < 0.001 for linear trend for both models) and of the same clinical order of magnitude for waist circumference (-0.52 and -0.44, respectively, P < 0.001 for linear trend for both models). CONCLUSION: The operationalized GDQS cutoffs did not change the performance of the GDQS and therefore are recommended for use to collect GDQS data in the future.

Development and Validation of a Novel Food-Based Global Diet Quality Score (GDQS).

BACKGROUND: Poor diet quality is a major driver of both classical malnutrition and noncommunicable disease (NCD) and was responsible for 22% of adult deaths in 2017. Most countries face dual burdens of undernutrition and NCDs, yet no simple global standard metric exists for monitoring diet quality in populations and population subgroups. OBJECTIVES: We aimed to develop an easy-to-use metric for nutrient adequacy and diet related NCD risk in diverse settings. METHODS: Using cross-sectional and cohort data from nonpregnant, nonlactating women of reproductive age in 10 African countries as well as China, India, Mexico, and the United States, we undertook secondary analyses to develop novel metrics of diet quality and to evaluate associations between metrics and nutrient intakes and adequacy, anthropometry, biomarkers, type 2 diabetes, and iteratively modified metric design to improve performance and to compare novel metric performance to that of existing metrics. RESULTS: We developed the Global Diet Quality Score (GDQS), a food-based metric incorporating a more comprehensive list of food groups than most existing diet metrics, and a simple means of scoring consumed amounts. In secondary analyses, the GDQS performed comparably with the Minimum Dietary Diversity - Women indicator in predicting an energy-adjusted aggregate measure of dietary protein, fiber, calcium, iron, zinc, vitamin A, folate, and vitamin B12 adequacy and with anthropometric and biochemical indicators of undernutrition (including underweight, anemia, and serum folate deficiency), and the GDQS also performed comparably or better than the Alternative Healthy Eating Index - 2010 in capturing NCD-related outcomes (including metabolic syndrome, change in weight and waist circumference, and incident type 2 diabetes). CONCLUSIONS: The simplicity of the GDQS and its ability to capture both nutrient adequacy and diet-related NCD risk render it a promising candidate for global monitoring platforms. Research is warranted to validate methods to operationalize GDQS assessment in population surveys, including a novel application-based 24-h recall system developed as part of this project.