Indicators for the ROI of Employee Wellness Programmes in South African Water Utility Organisations

Orientation: Our research emphasises the importance of conducting a thorough assessment of employee wellness programmes (EWPs). By analysing indicators of return on investment (ROI), we can gain a deeper understanding of the impact of such programmes, which are part of a participatory process. Research purpose: This study aimed to address a significant gap in the evaluation of EWPs in water utility organisations. We involved a panel of experts familiar with the organisation’s dynamics and internal processes in creating a unique framework of variables and indicators for evaluating ROI. Motivation for the study: There is little evidence of such programmes being evaluated at the local level, including within water utility organisations. Few studies focus on developing universally applicable ROI tools to measure the cost-effectiveness and social contribution of these programmes. Research approach/design and method: The study used a qualitative approach and employed the rigorous and widely respected Delphi technique to obtain consensus from a panel of experts. Main findings: The panel of experts reached a consensus on the qualitative and quantitative variables to include in a framework for evaluating the ROI of EWPs. Practical/managerial implications: The study found that determining the ROI of EWPs can be challenging as programmes often focus on the human aspects of organisations and less on cost factors. However, the study demonstrated the essential need for organisations to use a combination of subjective and objective indicators to evaluate the effects of EWPs, thereby enhancing their overall effectiveness. Contribution/value added: The study provides insights on subjective indicators reflecting non-monetary benefits and objective indicators reflecting cost factors

Vulnerable newborn types: analysis of subnational, population‐based birth cohorts for 541 285 live births in 23 countries, 2000–2021

Setting: Subnational, population-based birth cohort studies (n = 45) in 23 low-and middle-income countries (LMICs) spanning 2000–2021. Population: Liveborn infants. Methods: Subnational, population-based studies with high-quality birth outcome data from LMICs were invited to join the Vulnerable Newborn Measurement Collaboration. We defined distinct newborn types using gestational age (preterm [PT], term [T]), birthweight for gestational age using INTERGROWTH-21st standards (small for gestational age [SGA], appropriate for gestational age [AGA] or large for gestational age [LGA]), and birthweight (low birthweight, LBW [<2500 g], non- LBW) as ten types (using all three outcomes), six types (by excluding the birthweight categorisation), and four types (by collapsing the AGA and LGA categories). We defined small types as those with at least one classification of LBW, PT or SGA. We presented study characteristics, participant characteristics, data missingness, and prevalence of newborn types by region and study. Results: Among 541 285 live births, 476 939 (88.1%) had non-missing and plausible values for gestational age, birthweight and sex required to construct the newborn types. The median prevalences of ten types across studies were T+AGA+nonLBW (58.0%), T+LGA+nonLBW (3.3%), T+AGA+LBW (0.5%), T+SGA+nonLBW (14.2%), T+SGA+LBW (7.1%), PT+LGA+nonLBW (1.6%), PT+LGA+LBW (0.2%), PT+AGA+nonLBW (3.7%), PT+AGA+LBW (3.6%) and PT+SGA+LBW (1.0%). The median prevalence of small types (six types, 37.6%) varied across studies and within regions and was higher in Southern Asia (52.4%) than in Sub-Saharan Africa (34.9%). Conclusions: Further investigation is needed to describe the mortality risks associated with newborn types and understand the implications of this framework for local targeting of interventions to prevent adverse pregnancy outcomes in LMICs

Vulnerable newborn types : analysis of subnational, population‐based birth cohorts for 541 285 live births in 23 countries, 2000-2021

Setting: Subnational, population-basedbirth cohort studies (n = 45) in 23 low-andmiddle-incomecountries (LMICs) spanning 2000–2021.Population: Liveborn infants.Methods: Subnational, population-basedstudies with high-qualitybirth outcomedata from LMICs were invited to join the Vulnerable Newborn MeasurementCollaboration. We defined distinct newborn types using gestational age (preterm[PT], term [T]), birthweight for gestational age using INTERGROWTH-21ststandards(small for gestational age [SGA], appropriate for gestational age [AGA] or largefor gestational age [LGA]), and birthweight (low birthweight, LBW [<2500 g], non-LBW) as ten types (using all three outcomes), six types (by excluding the birthweightcategorisation), and four types (by collapsing the AGA and LGA categories). We definedsmall types as those with at least one classification of LBW, PT or SGA. Wepresented study characteristics, participant characteristics, data missingness, andprevalence of newborn types by region and study.Results: Among 541 285 live births, 476 939 (88.1%) had non-missingand plausiblevalues for gestational age, birthweight and sex required to construct the newborntypes. The median prevalences of ten types across studies were T+AGA+nonLBW(58.0%), T+LGA+nonLBW (3.3%), T+AGA+LBW (0.5%), T+SGA+nonLBW(14.2%), T+SGA+LBW (7.1%), PT+LGA+nonLBW (1.6%), PT+LGA+LBW (0.2%),PT+AGA+nonLBW (3.7%), PT+AGA+LBW (3.6%) and PT+SGA+LBW (1.0%). Themedian prevalence of small types (six types, 37.6%) varied across studies and withinregions and was higher in Southern Asia (52.4%) than in Sub-SaharanAfrica (34.9%).Conclusions: Further investigation is needed to describe the mortality risks associatedwith newborn types and understand the implications of this framework for localtargeting of interventions to prevent adverse pregnancy outcomes in LMICs.Setting: Subnational, population-basedbirth cohort studies (n = 45) in 23 low-andmiddle-incomecountries (LMICs) spanning 2000–2021.Population: Liveborn infants.Methods: Subnational, population-basedstudies with high-qualitybirth outcomedata from LMICs were invited to join the Vulnerable Newborn MeasurementCollaboration. We defined distinct newborn types using gestational age (preterm[PT], term [T]), birthweight for gestational age using INTERGROWTH-21ststandards(small for gestational age [SGA], appropriate for gestational age [AGA] or largefor gestational age [LGA]), and birthweight (low birthweight, LBW [<2500 g], non-LBW) as ten types (using all three outcomes), six types (by excluding the birthweightcategorisation), and four types (by collapsing the AGA and LGA categories). We definedsmall types as those with at least one classification of LBW, PT or SGA. Wepresented study characteristics, participant characteristics, data missingness, andprevalence of newborn types by region and study.Results: Among 541 285 live births, 476 939 (88.1%) had non-missingand plausiblevalues for gestational age, birthweight and sex required to construct the newborntypes. The median prevalences of ten types across studies were T+AGA+nonLBW(58.0%), T+LGA+nonLBW (3.3%), T+AGA+LBW (0.5%), T+SGA+nonLBW(14.2%), T+SGA+LBW (7.1%), PT+LGA+nonLBW (1.6%), PT+LGA+LBW (0.2%),PT+AGA+nonLBW (3.7%), PT+AGA+LBW (3.6%) and PT+SGA+LBW (1.0%). Themedian prevalence of small types (six types, 37.6%) varied across studies and withinregions and was higher in Southern Asia (52.4%) than in Sub-SaharanAfrica (34.9%).Conclusions: Further investigation is needed to describe the mortality risks associatedwith newborn types and understand the implications of this framework for localtargeting of interventions to prevent adverse pregnancy outcomes in LMICs.A

Neonatal mortality risk of vulnerable newborns : a descriptive analysis of subnational, population‐based birth cohorts for 238 143 live births in low‐ and middle‐income settings from 2000 to 2017

Objective: We aimed to understand the mortality risks of vulnerable newborns (defined as preterm and/or born weighing smaller or larger compared to a standard population), in low-and middle-income countries (LMICs). Design: Descriptive multi-country, secondary analysis of individual-level study data of babies born since 2000. Setting: Sixteen subnational, population-based studies from nine LMICs in sub-Saharan Africa, Southern and Eastern Asia, and Latin America. Population: Live birth neonates. Methods: We categorically defined five vulnerable newborn types based on size (large-or appropriate-or small-for-gestational age [LGA, AGA, SGA]), and term (T) and preterm (PT): T + LGA, T + SGA, PT + LGA, PT + AGA, and PT + SGA, with T + AGA (reference). A 10-type definition included low birthweight (LBW) and non-LBW, and a four-type definition collapsed AGA/LGA into one category. We performed imputation for missing birthweights in 13 of the studies. Main Outcome Measures: Median and interquartile ranges by study for the prevalence, mortality rates and relative mortality risks for the four, six and ten type classification. Results: There were 238 143 live births with known neonatal status. Four of the six types had higher mortality risk: T + SGA (median relative risk [RR] 2.8, interquartile range [IQR] 2.0–3.2), PT + LGA (median RR 7.3, IQR 2.3–10.4), PT + AGA (median RR 6.0, IQR 4.4–13.2) and PT + SGA (median RR 10.4, IQR 8.6–13.9). T + SGA, PT + LGA and PT + AGA babies who were LBW, had higher risk compared with non-LBW babies. Conclusions: Small and/or preterm babies in LIMCs have a considerably increased mortality risk compared with babies born at term and larger. This classification system may advance the understanding of the social determinants and biomedical risk factors along with improved treatment that is critical for newborn health

Vulnerable newborn types: analysis of subnational, population‐based birth cohorts for 541 285 live births in 23 countries, 2000–2021

Objective: To examine prevalence of novel newborn types among 541 285 live births in 23 countries from 2000 to 2021. Design: Descriptive multi-country secondary data analysis. Setting: Subnational, population-based birth cohort studies (n = 45) in 23 low- and middle-income countries (LMICs) spanning 2000–2021. Population: Liveborn infants. Methods: Subnational, population-based studies with high-quality birth outcome data from LMICs were invited to join the Vulnerable Newborn Measurement Collaboration. We defined distinct newborn types using gestational age (preterm [PT], term [T]), birthweight for gestational age using INTERGROWTH-21st standards (small for gestational age [SGA], appropriate for gestational age [AGA] or large for gestational age [LGA]), and birthweight (low birthweight, LBW [<2500 g], nonLBW) as ten types (using all three outcomes), six types (by excluding the birthweight categorisation), and four types (by collapsing the AGA and LGA categories). We defined small types as those with at least one classification of LBW, PT or SGA. We presented study characteristics, participant characteristics, data missingness, and prevalence of newborn types by region and study. Results: Among 541 285 live births, 476 939 (88.1%) had non-missing and plausible values for gestational age, birthweight and sex required to construct the newborn types. The median prevalences of ten types across studies were T+AGA+nonLBW (58.0%), T+LGA+nonLBW (3.3%), T+AGA+LBW (0.5%), T+SGA+nonLBW (14.2%), T+SGA+LBW (7.1%), PT+LGA+nonLBW (1.6%), PT+LGA+LBW (0.2%), PT+AGA+nonLBW (3.7%), PT+AGA+LBW (3.6%) and PT+SGA+LBW (1.0%). The median prevalence of small types (six types, 37.6%) varied across studies and within regions and was higher in Southern Asia (52.4%) than in Sub-Saharan Africa (34.9%). Conclusions: Further investigation is needed to describe the mortality risks associated with newborn types and understand the implications of this framework for local targeting of interventions to prevent adverse pregnancy outcomes in LMICs

Neonatal mortality risk of vulnerable newborns : a descriptive analysis of subnational, population‐based birth cohorts for 238 143 live births in low‐ and middle‐income settings from 2000 to 2017

Objective: We aimed to understand the mortality risks of vulnerable newborns (defined as preterm and/or born weighing smaller or larger compared to a standard population), in low-and middle-income countries (LMICs).Design: Descriptive multi-country, secondary analysis of individual-level study data of babies born since 2000.Setting: Sixteen subnational, population-based studies from nine LMICs in sub-Saharan Africa, Southern and Eastern Asia, and Latin America. Population: Live birth neonates.Methods: We categorically defined five vulnerable newborn types based on size (large-or appropriate-or small-for-gestational age [LGA, AGA, SGA]), and term (T) and preterm (PT): T + LGA, T + SGA, PT + LGA, PT + AGA, and PT + SGA, with T + AGA (reference). A 10-type definition included low birthweight (LBW) and non-LBW, and a four-type definition collapsed AGA/LGA into one category. We performed imputation for missing birthweights in 13 of the studies.Main Outcome Measures: Median and interquartile ranges by study for the prevalence, mortality rates and relative mortality risks for the four, six and ten type classification. Results: There were 238 143 live births with known neonatal status. Four of the six types had higher mortality risk: T + SGA (median relative risk [RR] 2.8, interquartile range [IQR] 2.0–3.2), PT + LGA (median RR 7.3, IQR 2.3–10.4), PT + AGA (median RR 6.0, IQR 4.4–13.2) and PT + SGA (median RR 10.4, IQR 8.6–13.9). T + SGA, PT + LGA and PT + AGA babies who were LBW, had higher risk compared with non-LBW babies.Conclusions: Small and/or preterm babies in LIMCs have a considerably increasedmortality risk compared with babies born at term and larger. This classification systemmay advance the understanding of the social determinants and biomedical riskfactors along with improved treatment that is critical for newborn health.Objective: We aimed to understand the mortality risks of vulnerable newborns (defined as preterm and/or born weighing smaller or larger compared to a standard population), in low-and middle-income countries (LMICs).Design: Descriptive multi-country, secondary analysis of individual-level study data of babies born since 2000.Setting: Sixteen subnational, population-based studies from nine LMICs in sub-Saharan Africa, Southern and Eastern Asia, and Latin America. Population: Live birth neonates.Methods: We categorically defined five vulnerable newborn types based on size (large-or appropriate-or small-for-gestational age [LGA, AGA, SGA]), and term (T) and preterm (PT): T + LGA, T + SGA, PT + LGA, PT + AGA, and PT + SGA, with T + AGA (reference). A 10-type definition included low birthweight (LBW) and non-LBW, and a four-type definition collapsed AGA/LGA into one category. We performed imputation for missing birthweights in 13 of the studies.Main Outcome Measures: Median and interquartile ranges by study for the prevalence, mortality rates and relative mortality risks for the four, six and ten type classification. Results: There were 238 143 live births with known neonatal status. Four of the six types had higher mortality risk: T + SGA (median relative risk [RR] 2.8, interquartile range [IQR] 2.0–3.2), PT + LGA (median RR 7.3, IQR 2.3–10.4), PT + AGA (median RR 6.0, IQR 4.4–13.2) and PT + SGA (median RR 10.4, IQR 8.6–13.9). T + SGA, PT + LGA and PT + AGA babies who were LBW, had higher risk compared with non-LBW babies.Conclusions: Small and/or preterm babies in LIMCs have a considerably increasedmortality risk compared with babies born at term and larger. This classification systemmay advance the understanding of the social determinants and biomedical riskfactors along with improved treatment that is critical for newborn health.A

Small babies, big risks : global estimates of prevalence and mortality for vulnerable newborns to accelerate change and improve counting

Small newborns are vulnerable to mortality and lifelong loss of human capital. Measures of vulnerability previously focused on liveborn low-birthweight (LBW) babies, yet LBW reduction targets are off-track. There are two pathways to LBW, preterm birth and fetal growth restriction (FGR), with the FGR pathway resulting in the baby being small for gestational age (SGA). Data on LBW babies are available from 158 (81%) of 194 WHO member states and the occupied Palestinian territory, including east Jerusalem, with 113 (58%) having national administrative data, whereas data on preterm births are available from 103 (53%) of 195 countries and areas, with only 64 (33%) providing national administrative data. National administrative data on SGA are available for only eight countries. Global estimates for 2020 suggest 13·4 million livebirths were preterm, with rates over the past decade remaining static, and 23·4 million were SGA. In this Series paper, we estimated prevalence in 2020 for three mutually exclusive types of small vulnerable newborns (SVNs; preterm non-SGA, term SGA, and preterm SGA) using individual-level data (2010–20) from 23 national datasets (∼110 million livebirths) and 31 studies in 18 countries (∼0·4 million livebirths). We found 11·9 million (50% credible interval [Crl] 9·1–12·2 million; 8·8%, 50% Crl 6·8–9·0%) of global livebirths were preterm non-SGA, 21·9 million (50% Crl 20·1–25·5 million; 16·3%, 14·9–18·9%) were term SGA, and 1·5 million (50% Crl 1·2–4·2 million; 1·1%, 50% Crl 0·9–3·1%) were preterm SGA. Over half (55·3%) of the 2·4 million neonatal deaths worldwide in 2020 were attributed to one of the SVN types, of which 73·4% were preterm and the remainder were term SGA. Analyses from 12 of the 23 countries with national data (0·6 million stillbirths at ≥22 weeks gestation) showed around 74% of stillbirths were preterm, including 16·0% preterm SGA and approximately one-fifth of term stillbirths were SGA. There are an estimated 1·9 million stillbirths per year associated with similar vulnerability pathways; hence integrating stillbirths to burden assessments and relevant indicators is crucial. Data can be improved by counting, weighing, and assessing the gestational age of every newborn, whether liveborn or stillborn, and classifying small newborns by the three vulnerability types. The use of these more specific types could accelerate prevention and help target care for the most vulnerable babies