Department of Population, Family and Reproductive Health
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Item Counting adolescents in: the development of an adolescent health indicator framework for population-based settings(Elsevier Ltd., 2023) Manu, A.Changing realities in low- and middle-income countries (LMICs) in terms of inequalities, urbanization, globalization, migration, and economic adversity shape adolescent development and health, as well as successful transitions be tween adolescence and young adulthood. It is estimated that 90% of adolescents live in LMICs in 2019, but inade quate data exist to inform evidence-based and concerted policies and programs tailored to address the distinctive developmental and health needs of adolescents. Population-based data surveillance such as Health and Demographic Surveillance Systems (HDSS) and school-based surveys provide access to a well-defined population and provide cost-effective opportunities to fill in data gaps about adolescent health and well-being by collecting population representative longitudinal data. The Africa Research Implementation Science and Education (ARISE) Network, therefore, systematically developed adolescent health and well-being indicators and a questionnaire for measuring these indicators that can be used in population-based LMIC settings. We conducted a multistage collaborative and iterative process led by network members alongside consultation with health-domain and adolescent health experts globally. Seven key domains emerged from this process: socio-demographics, health awareness and behaviors; nutrition; mental health; sexual and reproductive health; substance use; and healthcare utilization. For each domain, we generated a clear definition; rationale for inclusion; sub-domain descriptions, and a set of questions for mea surement. The ARISE Network will implement the questionnaire longitudinally (i.e., at two time-points one year apart) at ten sites in seven countries in sub-Saharan Africa and two countries in Asia. Integrating the questionnaire within established population-based data collection platforms such as HDSS and school settings can provide measured experiences of young people to inform policy and program planning and evaluation in LMICs and improve adolescent health and well-beingItem Associated factors of diet quality among people living with HIV/AIDS in Ghana(BMC Nutrition, 2024) Abdulai, K.; Torpey, T.; Kotoh, A.M.; Laar, A.Introduction : Nutrition is a very important element of a comprehensive care for people living with HIV/AIDS (PLHIV), especially in resource-constrained settings where malnutrition and food insecurity are common. Dietary diversity is a useful indication of nutritional adequacy (diet quality) in people of all ages. An optimally diverse diet strengthens the body’s immune system. Objective This study aimed to assess diet quality and its associated factors among PLHIV. Methods A facility-based cross-sectional study design was employed to select 440 PLHIV from two hospitals in the Eastern Region of Ghana. Dietary intakes were determined using 24-hour recall. A stadiometer and bioimpedance analysis machine were used to obtain anthropometric and body composition data. Diet quality was assessed using FAO’s individual dietary diversity score (IDDS) as a proxy. SPSS version 20 was used for analysis. Odds ratios and ordinal logistic regression were used to identify factors associated with diet quality among the PLHIV. P-value was set at 0.05. Results Most of the PLHIV (73%) consumed from ‘Starchy staple” food group. Less than 20% of the study sample consumed ‘Fruits’ and ‘Vegetables’ (17% and 14% respectively) a day before the survey. The mean IDDS was 4.11 (SD=1.29). Overall, most of the PLHIV (56%) had medium IDDS which is equivalent to “diet needing improvement’, 14% had higher IDDS (good diet), whiles about 31% of the participants actually had poor diet (lower IDDS). Associated factors of diet quality were age (AOR=0.966: 95%CI: 0.936–0.997: p=0.031), married (AOR=4.634: 95%CI: 1.329– 16.157: p=0.0016), separated (AOR=0.0203: 95%CI: .036–0.994: p=0.049), and daily meal frequency (AOR=0.441: 95%CI: .478–1.948: p=0.020). Overall, the model accounts for about 20% of the variation in diet quality of the participants (pseudo-R square=0.196). Conclusion This study demonstrates that most of the PLHIV did not consume good diet which may have an implication on their immune system, which is already under attack by HIV, and probably emerging infections. Age, marital status, and meal frequency were the variables that predicted diet quality among the study participants.