Social determinants of multimorbidity are poorly understood in clinical practice. This review aims to characterize the different multimorbidity patterns described in the literature while identifying the social and behavioral determinants that may affect their emergence and subsequent evolution. We searched PubMed, Embase, Scopus, Web of Science, Ovid MEDLINE, CINAHL Complete, PsycINFO and Google Scholar. In total, 97 studies were chosen from the 48,044 identified. Cardiometabolic, musculoskeletal, mental, and respiratory patterns were the most prevalent. Cardiometabolic multimorbidity profiles were common among men with low socioeconomic status, while musculoskeletal, mental and complex patterns were found to be more prevalent among women. Alcohol consumption and smoking increased the risk of multimorbidity, especially in men. While the association of multimorbidity with lower socioeconomic status is evident, patterns of mild multimorbidity, mental and respiratory related to middle and high socioeconomic status are also observed. The findings of the present review point to the need for further studies addressing the impact of multimorbidity and its social determinants in population groups where this problem remains invisible (e.g., women, children, adolescents and young adults, ethnic groups, disabled population, older people living alone and/or with few social relations), as well as further work with more heterogeneous samples (i.e., not only focusing on older people) and using more robust methodologies for better classification and subsequent understanding of multimorbidity patterns. Besides, more studies focusing on the social determinants of multimorbidity and its inequalities are urgently needed in low- and middle-income countries, where this problem is currently understudied.

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Background Childhood obesity poses a global health challenge. In recent years, there has been an increase in interventions that begin in pregnancy, putting the concept of early programming and early risk factors into practice. The present study aims to update the findings regarding interventions in the first 1000 days of life. Methods A systematic review based on the PRISMA guidelines was carried out in PubMed, WoS, Scopus and CINAHL to obtain the articles to be analysed. We included those studies published between 2016 and 2021. Human interventions that started within the first 1000 days of life and acted on at least one programming factor were included. Once selected, coding and quantitative content analysis was carried out to obtain a profile of the interventions during the first 1000 days. Results From all screened articles, 51 unique interventions, which met the selection criteria, were included. The majority of interventions (81%) took place in high-income areas. Almost all (86%) were targeted at the general population. The majority (54%) started in the second trimester of pregnancy. A clear majority (61%) ended at the time of birth. 44% of the interventions included all pregnant women. Only 48% of these interventions were focused on improving the nutritional status of the offspring in the short term. Most interventions collected the baby's weight at birth (68%). Conclusions It can be concluded that current interventions are not covering as many aspects as they should. Future research should be conducted more frequently in developing countries and target disadvantaged groups. These interventions should include all pregnant women, regardless of their nutritional status, aiming to cover as many programming factors as possible and extending through the first 1000 days of life, with body mass index or skinfolds as measures of effectiveness during this period.

Background: Childhood obesity poses a global health challenge. Despite efforts to reverse this situation in recent years, the figures remain high. In recent years, there has been an increase in interventions that begin in pregnancy, putting the concept of early programming into practice. The present study aims to update the findings regarding interventions in the first 1000 days of life. Methods: A systematic review of the literature was carried out in PubMed, WoS, Scopus and CINAHL to obtain the articles to be analysed. We included those studies published between 2016 and 2021. Human interventions that started within the first 1000 days of life and acted on at least one programming factor were included. Once selected, coding and quantitative content analysis was carried out to obtain a profile of the interventions during the first 1000 days. Results: From all screened articles, 51 unique interventions, which met the selection criteria, were included. The majority of interventions (81%) take place in developed areas. Almost all (86%) are targeted at the general population. The majority (54%) start in the second trimester of pregnancy. A clear majority (61%) end at the time of birth. 44% of the interventions include all pregnant women. Only 48% of these interventions are focused on improving the nutritional status of the offspring in the short term. Most interventions collect the baby's weight at birth (68%). Conclusions: It can be concluded that current interventions are not covering as many aspects as they should. Future research should be conducted more frequently in developing countries and target disadvantaged groups. These interventions should include all pregnant women, aiming to cover as many programming factors as possible and extending through the first 1000 days of life, with BMI or skinfolds as measures of effectiveness during this period.

Multimorbidity is a growing challenge, associated with reduced quality of life, increased disability, increased health care utilisation, and increased mortality. There is a need to identify associations among patterns of chronic conditions and social determinants of health in the local context of specific population groups. This work aims to respond to this gap, detecting patterns of multimorbidity and their inequalities in the province of Cadiz (South Spain). A cross-sectional study was conducted through a telephone interview in population over 50 years of age. We use Latent Class Analysis to identify patterns from 31 health chronic conditions and to detect associations with social determinants. The model derived five patterns, with an entropy of 0.728, which were as follows: ‘Relative Healthy’, ‘Cardiovascular’, ‘Musculoskeletal’, ‘Musculoskeletal and Mental’ and ‘Complex Multimorbidity’. Patterns showed significant differences in the covariates, with results in age, education, income level, and health services use being of particular interest. All four patterns with more conditions also showed lower scores on the two dimensions of SF12 scale. We also found significant differences among patterns and districts in Jerez. These results highlight the existence of social inequalities in multimorbidity at the local level that should be addressed by implementing policies targeting the most vulnerable social groups in Cadiz.