Maternal and offspring intelligence in relation to BMI across childhood and adolescence.

OBJECTIVE: The present study tested the association between both mothers' and offspring's intelligence and offspring's body mass index (BMI) in youth. METHOD: Participants were members of the National Longitudinal Survey of Youth 1979 (NLSY-79) Children and Young Adults cohort (n = 11,512) and their biological mothers who were members of the NLSY-79 (n = 4932). Offspring's IQ was measured with the Peabody Individual Achievement Test (PIAT). Mothers' IQ was measured with the Armed Forces Qualification Test (AFQT). A series of regression analyses tested the association between IQ and offspring's BMI by age group, while adjusting for pre-pregnancy BMI and family SES. The analyses were stratified by sex and ethnicity (non-Black and non-Hispanic, Black, and Hispanic). RESULTS: The following associations were observed in the fully adjusted analyses. For the non-Blacks and non-Hispanics, a SD increment in mothers' IQ was negatively associated with daughters' BMI across all age-groups, ranging from ß = -0.12 (95% CI -0.22 to -0.02, p = 0.021) in late childhood, to ß = -0.17 (95% C.I. -0.27 to -0.07, p = 0001), in early adolescence and a SD increment in boys' IQ was positively associated with their BMI in early adolescence ß = 0.09 (95% CI 0.01-0.18, p = 0.031). For Blacks, there was a non-linear relationship between mothers' IQ and daughters' BMI across childhood and between girls' IQ and BMI across adolescence. There was a positive association between mothers' IQ and sons' BMI in early adolescence (ß = 0.17, 95% CI 0.02-0.32, p = 0.030). For Hispanic boys, there was a positive IQ-BMI association in late childhood (ß = 0.19, 95% CI 0.05-0.33, p = 0.008) and early adolescence (ß = 0.17, 95% CI 0.04-0.31, p = 0.014). CONCLUSION: Mothers' IQ and offspring's IQ were associated with offspring's BMI. The relationships varied in direction and strength across ethnicity, age group and sex. Obesity interventions may benefit from acknowledging the heterogeneous influence that intelligence has on childhood BMI.

Intelligence in youth and health behaviours in middle age.

OBJECTIVE: We investigated the association between intelligence in youth and a range of health-related behaviours in middle age. METHOD: Participants were the 5347 men and women who responded to the National Longitudinal Survey of Youth 1979 (NLSY-79) 2012 survey. IQ was recorded with the Armed Forces Qualification Test (AFQT) when participants were aged 15 to 23 years of age. Self-reports on exercise (moderate activity, vigorous activity, and strength training), dietary, smoking, drinking, and oral health behaviours were recorded when participants were in middle age (mean age = 51.7 years). A series of regression analyses tested for an association between IQ in youth and the different health related behaviours in middle age, while adjusting for childhood socio-economic status (SES) and adult SES. RESULTS: Higher IQ in youth was significantly associated with the following behaviours that are beneficial to health: being more likely to be able to do moderate cardiovascular activity (Odds Ratio, 95% CI) (1.72, 1.35 to 2.20, p < .001) and strength training (1.61, 1.37 to 1.90, p < .001); being less likely to have had a sugary drink in the previous week (0.75, 0.71 to 0.80, p < .001); a lower likelihood of drinking alcohol heavily (0.67, 0.61 to 0.74, p < .001); being less likely to smoke (0.60, 0.56 to 0.65, p < .001); being more likely to floss (1.47, 1.35 to 1.59, p < .001); and being more likely to say they "often" read the nutritional information (1.20, 1.09 to 1.31, p < .001) and ingredients (1.24, 1.12 to 1.36, p < .001) on food packaging compared to always reading them. Higher IQ was also linked with dietary behaviours that may or may not be linked with poorer health outcomes (i.e. being more likely to have skipped a meal (1.10, 1.03 to 1.17, p = .005) and snacked between meals (1.37, 1.26 to 1.50, p < .001) in the previous week). An inverted u-shaped association was also found between IQ and the number of meals skipped per week. Higher IQ was also linked with behaviours that are known to be linked with poorer health (i.e. a higher likelihood of drinking alcohol compared to being abstinent from drinking alcohol (1.58, 1.47 to 1.69, p < .001)). A u-shaped association was found between IQ and the amount of alcohol consumed per week and an inverted u-shaped association was found between IQ and the number of cigarettes smoked a day. Across all outcomes, adjusting for childhood SES tended to attenuate the estimated effect size only slightly. Adjusting for adult SES led to more marked attenuation but statistical significance was maintained in most cases. CONCLUSION: In the present study, a higher IQ in adolescence was associated with a number of healthier behaviours in middle age. In contrast to these results, a few associations were also identified between higher intelligence and behaviours that may or may not be linked with poor health (i.e. skipping meals and snacking between meals) and with behaviours that are known to be linked with poor health (i.e. drinking alcohol and the number of cigarettes smoked). To explore mechanisms of association, future studies could test for a range of health behaviours as potential mediators between IQ and morbidity or mortality in later life.

Intelligence in youth and mental health at age 50.

BACKGROUND: Few cognitive epidemiology studies on mental health have focused on the links between pre-morbid intelligence and self-reports of common mental disorders, such as depression, sleep difficulties, and mental health status. The current study examines these associations in 50-year-old adults. METHODS: The study uses data from the 5793 participants in the National Longitudinal Survey of Youth 1979 cohort (NLSY-79) who responded to questions on mental health at age 50 and had IQ measured with the Armed Forces Qualification Test (AFQT) when they were aged between 15 and 23 years in 1980. Mental health outcomes were: life-time diagnosis of depression; the mental component score of the 12-item short-form Health Survey (SF-12); the 7-item Center for Epidemiological Studies Depression Scale (CES-D); and a summary measure of sleep difficulty. RESULTS & CONCLUSION: Higher intelligence in youth is associated with a reduced risk of self-reported mental health problems at age 50, with age-at-first-interview and sex adjusted Bs as follows: CES-depression (B = - 0.16, C.I. - 0.19 to - 0.12, p < 0.001), sleep difficulties (B = - 0.11, C.I. - 0.13 to - 0.08, p < 0.001), and SF-12 mental health status (OR = 0.78, C.I. 0.72 to 0.85, p < 0.001; r = - 0.03 p = 0.075). Conversely, intelligence in youth is linked with an increased risk of receiving a diagnosis of depression by the age of 50 (OR 1.11, C.I. 1.01 to 1.22, p = 0.024; r = 0.03, p = 0.109). No sex differences were observed in the associations. Adjusting for adult SES accounted for most of the association between IQ and the mental health outcomes, except for having reported a diagnosis of depression, in which case adjusting for adult SES led to an increase in the size of the positive association (OR = 1.32, C.I. 1.16 to 1.51, p < 0.001).

Intelligence in youth and health at age 50.

BACKGROUND: The link between intelligence in youth and all-cause mortality in later-life is well established. To better understand this relationship, the current study examines the links between pre-morbid intelligence and a number of specific health outcomes at age 50 using the NLSY-1979 cohort. METHODS: Participants were the 5793 participants in the NLSY-79 who responded to questions about health outcomes at age 50. Sixteen health outcomes were examined: two were summary measures (physical health and functional limitation), 9 were diagnosed illness conditions, 4 were self-reported conditions, and one was a measure of general health status. Linear and logistic regressions were used, as appropriate, to examine the relationship between intelligence in youth and the health outcomes. Age, sex and both childhood and adult SES, and its sub-components - income, education, & occupational prestige - are all adjusted for separately. RESULTS & CONCLUSION: Higher pre-morbid intelligence is linked with better physical health at age 50, and a lower risk for a number of chronic health conditions. For example, a 1 SD higher score in IQ was significantly associated with increased odds of having good, very good, or excellent health, with an odds ratio of 1.70 (C.I. 1.55-1.86). Thirteen of the illness outcomes were significantly and negatively associated with IQ in youth; the odds ratios ranged from 0.85 for diabetes/high blood sugar to 0.65 for stroke, per one standard deviation higher score in IQ. Adjustment for childhood SES led to little attenuation but adult SES partially mediated the relationship for a number of conditions. Mediation by adult SES was not consistently explained by any one of its components-income, education, and occupation status. The current findings contribute to our understanding of lower intelligence as a risk factor for poor health and how this may contribute to health inequalities.

Can changes in spending on health and social care explain the recent mortality trends in Scotland? A protocol for an observational study.

INTRODUCTION: There have been steady reductions in mortality rates in the majority of high-income countries, including Scotland, since 1945. However, reductions in mortality rates have slowed down since 2012-2014 in these nations; and have reversed in some cases. Deaths among those aged 55+ explain a large amount of these changing mortality trends in Scotland. Increased pressures on health and social care services have been suggested as one factor explaining these changes. This paper outlines a protocol for the approach to testing the extent to which health and social care pressures can explain recent mortality trends in Scotland. Although a slower rate of mortality improvements have affected people of all ages, certain ages have been more negatively affected than the others. The current analyses will be run by age-band to test if the service pressure-mortality link varies across age-group. METHODS AND ANALYSIS: This will be an observational ecological study based on the Scottish population. The exposures of interest will be the absolute (primary outcome) and percentage (secondary outcome) change in real terms per capita spending on social and healthcare services between 2011 and 2017. The outcome of interest will be the absolute (primary outcome) and percentage (secondary outcome) change in age-standardised mortality rate between 2012 and 2018 for men and women separately. The units of analysis will be the 32 local authorities and the 14 territorial health boards. The analyses will be run for both all age-groups combined and for the following age bands: <1, 1-15, 16-44, 45-64, 65-74, 75-84 and 85+.A series of descriptive analyses will summarise the distribution of health and social care expenditure and mortality trends between 2011 and 2018. Linear regression analysis will be used to investigate the direct association between health care spending and mortality rates. ETHICS AND DISSEMINATION: The data used in this study will be publicly available and aggregated and will not be individually identifiable; therefore, ethical committee approval is not needed. This work will not result in the creation of a new data set. On completion, the study will be stored within the National Health Service research governance system. All of the results will be published once they have been shared with partner agencies.

Hypertension Development by Midlife and the Roles of Premorbid Cognitive Function, Sex, and Their Interaction.

Higher early-life cognitive function is associated with better later-life health outcomes, including hypertension. Associations between higher prior cognitive function and less hypertension persist even when accounting for socioeconomic status, but socioeconomic status-hypertension gradients are more pronounced in women. We predicted that differences in hypertension development between sexes might be associated with cognitive function and its interaction with sex, such that higher early-life cognitive function would be associated with lower hypertension risk more in women than in men. We used accelerated failure time modeling with the National Longitudinal Study of Youth 1979. Cognitive function was assessed in youth, when participants were aged between 14 and 21 years. Of 2572 men and 2679 women who completed all assessments, 977 men and 940 women reported hypertension diagnoses by 2015. Socioeconomic status in youth and adulthood were investigated as covariates, as were components of adult socioeconomic status: education, occupational status, and family income. An SD of higher cognitive function in youth was associated with reduced hypertension risk (acceleration factor: c=0.97; 95% CI, 0.96-0.99; P=0.001). The overall effect was stronger in women (sex×cognitive function: c=0.97; 95% CI, 0.94-0.99; P=0.010); especially, higher functioning women were less at risk than their male counterparts. This interaction was itself attenuated by a sex by family income interaction. People with better cognitive function in youth, especially women, are less likely to develop hypertension later in life. Income differences accounted for these associations. Possible causal explanations are discussed.

How youth cognitive and sociodemographic factors relate to the development of overweight and obesity in the UK and the USA: a prospective cross-cohort study of the National Child Development Study and National Longitudinal Study of Youth 1979.

OBJECTIVES: We investigated how youth cognitive and sociodemographic factors are associated with the aetiology of overweight and obesity. We examined both onset (who is at early risk for overweight and obesity) and development (who gains weight and when). DESIGN: Prospective cohort study. SETTING: We used data from the US National Longitudinal Study of Youth 1979 (NLSY) and the UK National Child Development Study (NCDS); most of both studies completed a cognitive function test in youth. PARTICIPANTS: 12 686 and 18 558 members of the NLSY and NCDS, respectively, with data on validated measures of youth cognitive function, youth socioeconomic disadvantage (eg, parental occupational class and time spent in school) and educational attainment. Height, weight and income data were available from across adulthood, from individuals' 20s into their 50s. PRIMARY AND SECONDARY OUTCOME MEASURES: Body mass index (BMI) for four time points in adulthood. We modelled gain in BMI using latent growth curve models to capture linear and quadratic components of change in BMI over time. RESULTS: Across cohorts, higher cognitive function was associated with lower overall BMI. In the UK, 1 SD higher score in cognitive function was associated with lower BMI (ß=-0.20, 95% CI -0.33 to -0.06 kg/m²). In America, this was true only for women (ß=-0.53, 95% CI -0.90 to -0.15 kg/m²), for whom higher cognitive function was associated with lower BMI. In British participants only, we found limited evidence for negative and positive associations, respectively, between education (ß=-0.15, 95% CI -0.26 to -0.04 kg/m²) and socioeconomic disadvantage (ß=0.33, 95% CI 0.23 to 0.43 kg/m²) and higher BMI. Overall, no cognitive or socioeconomic factors in youth were associated with longitudinal changes in BMI. CONCLUSIONS: While sociodemographic and particularly cognitive factors can explain some patterns in individuals' overall weight levels, differences in who gains weight in adulthood could not be explained by any of these factors.