Stunting remains a public health concern in developing countries. Factors related to stunting have been categorized using various frameworks. Family plays an important role in providing nutrients for children; however, no review specifies this aspect for identifying family characteristics related to stunting. This study aimed to identify family household characteristics related to stunting among children aged less than 5 years. A scoping review was undertaken with sources from PubMed, CINAHL, and Scopus, using the keywords “family characteristics” AND “growth”. Inclusion criteria were (1) correlational study; (2) published between 2018 and 31 July 2022; (3) families with children under the age of 5 years; and (4) independent variable any measure of stunting factors from family and household factors. Of 376 articles, only 20 met the inclusion criteria of the study. The family household characteristics included individual factors (sex age, history of diarrhea, and birthplace), family factors (family headship, primary caregiver/mother, social-cultural orientation, and family system factors), and environmental factors. Various child variables, family factors, and environmental factors (the type of home, floor type, water access, source of drinking water, and household electricity) were identified as being associated with stunting. Therefore, these factors should be evaluated to prevent and control stunting, and they should be incorporated into health programs targeting stunting.

Aim: As individuals age, they are expected to experience a natural progression that usually involves a slight and permanent decrease in bodily functions and physical abilities. Despite this, many older people remain active in the workforce. Purpose: This study seeks to explore the correlation between the health conditions, disabilities, social factors, and demographic circumstances of elderly individuals engaged in both formal and informal employment sectors. Methods: This study utilizes an observational analytical method with a cross-sectional structure. The participants in the research involved all individuals aged 60 years and above who met the outlined criteria, totaling 15,034,946 respondents. The data analysis was conducted using multivariate logistic regression in Model II. Results: Overall, most older adults are working in informal jobs. Moreover, most respondents are 60– 69 years old, married, have a primary school certificate, own health insurance and a house, and live with family. In addition, the multivariate analysis shows the relationship between each variable and the informal sector working elderly. It is known that older women have a 1.45 times higher limited educational background, not having savings is 1.21 times, rural areas living 1.93 times, not being the head of the family is linked 1.34 times, poor health conditions are 1.01 times, and having a disability has a 1.20 times higher likelihood of informal-sector employment. Conclusion: Several variables are assigned as the determinants that increase the number of elderly working in informal sectors, including gender, education level, savings ownership, living areas, head of the family role, health status, and disability.