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A variety of new research approaches are providing new ways to better understand the developmental mechanisms through which poverty affects children's development. However, studies of child poverty often characterize samples using different markers of poverty, making it difficult to contrast and reconcile findings across studies. Ideally, scientists can maximize the benefits of multiple disciplinary approaches if data from different kinds of studies can be directly compared and linked. Here, we suggest that individual studies can increase their potential usefulness by including a small set of common key variables to assess socioeconomic status and family income. These common variables can be used to (a) make direct comparisons between studies and (b) better enable diversity of subjects and aggregation of data regarding many facets of poverty that would be difficult within any single study. If kept brief, these items can be easily balanced with the need for investigators to creatively address the research questions in their specific study designs. To advance this goal, we identify a small set of brief, low‐burden consensus measures that researchers could include in their studies to increase cross‐study data compatibility. These US based measures can be adopted for global contexts., Research on child poverty employs a variety of different indices of poverty, making it difficult to contrast and reconcile findings across studies. This Open Access paper provides a small set of brief key variables to assess socio‐economic status and family income, allowing studies to be directly compared. This measure can be used to make direct comparisons between studies and better enable diversity of subjects and aggregation of data regarding many facets of poverty that would be difficult within any single study.

Background Consumer nutrition environment measures are important to understanding the food environment, which affects individual dietary intake. A nutrition environment measures survey for supermarkets (NEMS-S) has been designed on paper for use in Guatemala. However, a paper survey is not an inconspicuous data collection method. Objective To design, pilot test, and validate the Guatemala NEMS-S in the form of a mobile phone application (mobile app). Methods CommCare, a free and open-source software application, was used to design the NEMS-S for Guatemala in the form of a mobile app. Two raters tested the mobile app in a single Guatemalan supermarket. Both the interrater and the test—retest reliability of the mobile app were determined using percent agreement and Cohen's kappa score and compared with the interrater and test—retest reliability of the paper version. Results Interrater reliability was very high between the paper survey and the mobile app (Cohen's kappa > 0.90). Test—retest reliability ranged from kappa 0.78 to 0.91. Between two certified NEMS-S raters, survey completion time using the mobile app was 5 minutes less than that with the paper form (35 vs. 40 minutes). Conclusions The NEMS-S mobile app provides for more rapid data collection, with equivalent reliability and validity to the NEMS-S paper version, with advantages over a paper-based survey of multiple language capability and concomitant data entry.

A statistical survey of households based upon questionnaires distributed via primary schools has been carried out in five wards of Dar es Salaam, Tanzania, to estimate disposal frequencies (number of items disposed per week) for newsprint, metal cans, glass and plastic containers and plastic shopping bags. Plastic shopping bags are disposed most frequently while glass containers are disposed least frequently. The statistical distribution of disposal frequencies, which seems to be influenced by household income, is well described by Poisson distribution. Disposal frequencies are mutually correlated at 95% level of probability despite the differences in disposal patterns of individual households.

The study reported here describes the links between non-farm employment and child nutritional status in rural coastal Kenya using a model adapted from an operational model commonly used in nutrition planning. Four studies were conducted in 1994 and 1995 in a community in Kwale district. Three of these studies were nonfarm employment and subsistence food production, household income and food accessibility, and maternal employment and child care and house health environment. The findings of these three studies were used in the design of the fourth study which assessed the whole model.Households which combined both NFE and agricultural sources of income had higher total incomes than those which depended on only one source. The relation between non-farm employment and nutritional status was weak. There was a positive relation between household income and the level of household food expenditure, which, in turn, was positively associated with long-term nutritional status of children. Higher energy intake was associated with food diversity and increased with income level. The sources of differences in food diversity within income groups were not sought. Household income and time spent in the non-farm activities per woman had no direct linear effects on the components of child care. However, income did affect housing quality, while time affected household sanitation/hygiene. Maternal employment had no effect on the components of child care and household-living conditions when controlling for the age of the youngest child, mother's education and household income. This is attributed to the fact that the mother had a lot of "spare time". Hence, this analysis suggests that non-farm employment can open an opportunity to provide for enhanced child's long-term nutritional status through the effect of total income on nutrient intake and through purchased goods that improve housing quality. Women's time in non-farm employment, although affecting house sanitation/hygiene, does not have to compromise the nutritional status of children. It is concluded that the framework used by households to allocate their resources of time and income is different from the framework used for programming and policy development. The role of non-economic factors in the difference between two frameworks is suggested as a focus for future research.

The study reported here describes the links between non-farm employment and child nutritional status in rural coastal Kenya using a model adapted from an operational model commonly used in nutrition planning. Four studies were conducted in 1994 and 1995 in a community in Kwale district. Three of these studies were nonfarm employment and subsistence food production, household income and food accessibility, and maternal employment and child care and house health environment. The findings of these three studies were used in the design of the fourth study which assessed the whole model.Households which combined both NFE and agricultural sources of income had higher total incomes than those which depended on only one source. The relation between non-farm employment and nutritional status was weak. There was a positive relation between household income and the level of household food expenditure, which, in turn, was positively associated with long-term nutritional status of children. Higher energy intake was associated with food diversity and increased with income level. The sources of differences in food diversity within income groups were not sought. Household income and time spent in the non-farm activities per woman had no direct linear effects on the components of child care. However, income did affect housing quality, while time affected household sanitation/hygiene. Maternal employment had no effect on the components of child care and household-living conditions when controlling for the age of the youngest child, mother's education and household income. This is attributed to the fact that the mother had a lot of "spare time". Hence, this analysis suggests that non-farm employment can open an opportunity to provide for enhanced child's long-term nutritional status through the effect of total income on nutrient intake and through purchased goods that improve housing quality. Women's time in non-farm employment, although affecting house sanitation/hygiene, does not have to compromise the nutritional status of children. It is concluded that the framework used by households to allocate their resources of time and income is different from the framework used for programming and policy development. The role of non-economic factors in the difference between two frameworks is suggested as a focus for future research.